%PDF-1.3
1 0 obj
<< /Type /Catalog
/Outlines 2 0 R
/Pages 3 0 R >>
endobj
2 0 obj
<< /Type /Outlines /Count 0 >>
endobj
3 0 obj
<< /Type /Pages
/Kids [6 0 R
9 0 R
11 0 R
13 0 R
15 0 R
17 0 R
19 0 R
21 0 R
23 0 R
25 0 R
27 0 R
]
/Count 11
/Resources <<
/ProcSet 4 0 R
/Font <<
/F1 8 0 R
>>
>>
/MediaBox [0.000 0.000 841.890 595.280]
>>
endobj
4 0 obj
[/PDF /Text ]
endobj
5 0 obj
<<
/Producer (iText Version: 7.1.0)
/CreationDate (D:20221007125954+00'00')
/ModDate (D:20221007125954+00'00')
/Title (Where To Download Approximating Integrals Via Monte Carlo And Deterministic Methods [PDF] - blog.payboy.biz)
/Subject (blog.payboy.biz)
/Author (Bogle-L'Ouverture Publications)
/Keywords (Read Free Where To Download Approximating Integrals Via Monte Carlo And Deterministic Methods [PDF] - blog.payboy.biz)
>>
endobj
6 0 obj
<< /Type /Page
/MediaBox [0.000 0.000 841.890 595.280]
/Parent 3 0 R
/Contents 7 0 R
>>
endobj
7 0 obj
<<
/Length 4537 >>
stream
0.000 0.000 0.000 rg
BT 34.016 519.271 Td /F1 25.5 Tf [(Approximating Integrals Via Monte Carlo And Deterministic Methods)] TJ ET
BT 34.016 470.755 Td /F1 12.8 Tf [(As recognized, adventure as capably as experience practically lesson, amusement, as well as conformity can be gotten by just checking )] TJ ET
BT 34.016 455.187 Td /F1 12.8 Tf [(out a book )] TJ ET
BT 97.103 455.187 Td /F1 12.8 Tf [(Approximating Integrals Via Monte Carlo And Deterministic Methods)] TJ ET
BT 481.859 455.187 Td /F1 12.8 Tf [( as a consequence it is not directly done, you could )] TJ ET
BT 34.016 439.619 Td /F1 12.8 Tf [(undertake even more concerning this life, roughly the world. )] TJ ET
BT 34.016 408.751 Td /F1 12.8 Tf [(We have the funds for you this proper as with ease as simple pretension to get those all. We have enough money Approximating )] TJ ET
BT 34.016 393.184 Td /F1 12.8 Tf [(Integrals Via Monte Carlo And Deterministic Methods and numerous ebook collections from fictions to scientific research in any way. )] TJ ET
BT 34.016 377.616 Td /F1 12.8 Tf [(among them is this Approximating Integrals Via Monte Carlo And Deterministic Methods that can be your partner.)] TJ ET
BT 34.016 321.248 Td /F1 12.8 Tf [(Nonlinear Time Series)] TJ ET
BT 160.126 321.248 Td /F1 12.8 Tf [( Randal Douc 2014-01-06 Designed for researchers and students, Nonlinear Times Series: Theory, Methods and )] TJ ET
BT 34.016 305.680 Td /F1 12.8 Tf [(Applications with R Examples familiarizes readers with the principles behind nonlinear time series models-without overwhelming them )] TJ ET
BT 34.016 290.113 Td /F1 12.8 Tf [(with difficult mathematical developments. By focusing on basic principles and theory, the authors give readers the background required)] TJ ET
BT 34.016 274.545 Td /F1 12.8 Tf [(Automatic Nonuniform Random Variate Generation)] TJ ET
0.000 0.000 0.000 RG
0.255 w 0 J [ ] 0 d
34.016 272.441 m 322.421 272.441 l S
BT 322.421 274.545 Td /F1 12.8 Tf [( Wolfgang Hörmann 2013-06-29 The recent concept of universal \(also called )] TJ ET
BT 34.016 258.977 Td /F1 12.8 Tf [(automatic or black-box\) random variate generation can only be found dispersed in the literature. Being unique in its overall organization, )] TJ ET
BT 34.016 243.409 Td /F1 12.8 Tf [(the book covers not only the mathematical and statistical theory but also deals with the implementation of such methods. All algorithms )] TJ ET
BT 34.016 227.842 Td /F1 12.8 Tf [(introduced in the book are designed for practical use in simulation and have been coded and made available by the authors. Examples )] TJ ET
BT 34.016 212.274 Td /F1 12.8 Tf [(of possible applications of the presented algorithms \(including option pricing, VaR and Bayesian statistics\) are presented at the end of )] TJ ET
BT 34.016 196.706 Td /F1 12.8 Tf [(the book.)] TJ ET
BT 34.016 181.138 Td /F1 12.8 Tf [(Contemporary Computational Mathematics - A Celebration of the 80th Birthday of Ian Sloan)] TJ ET
0.255 w 0 J [ ] 0 d
34.016 179.035 m 550.620 179.035 l S
BT 550.620 181.138 Td /F1 12.8 Tf [( Josef Dick 2018-05-23 This book is a tribute )] TJ ET
BT 34.016 165.571 Td /F1 12.8 Tf [(to Professor Ian Hugh Sloan on the occasion of his 80th birthday. It consists of nearly 60 articles written by international leaders in a )] TJ ET
BT 34.016 150.003 Td /F1 12.8 Tf [(diverse range of areas in contemporary computational mathematics. These papers highlight the impact and many achievements of )] TJ ET
BT 34.016 134.435 Td /F1 12.8 Tf [(Professor Sloan in his distinguished academic career. The book also presents state of the art knowledge in many computational fields )] TJ ET
BT 34.016 118.867 Td /F1 12.8 Tf [(such as quasi-Monte Carlo and Monte Carlo methods for multivariate integration, multi-level methods, finite element methods, )] TJ ET
BT 34.016 103.300 Td /F1 12.8 Tf [(uncertainty quantification, spherical designs and integration on the sphere, approximation and interpolation of multivariate functions, )] TJ ET
BT 34.016 87.732 Td /F1 12.8 Tf [(oscillatory integrals, and in general in information-based complexity and tractability, as well as in a range of other topics. The book also )] TJ ET
BT 34.016 72.164 Td /F1 12.8 Tf [(tells the life story of the renowned mathematician, family man, colleague and friend, who has been an inspiration to many of us. The )] TJ ET
BT 34.016 56.596 Td /F1 12.8 Tf [(reader may especially enjoy the story from the perspective of his family, his wife, his daughter and son, as well as grandchildren, who )] TJ ET
endstream
endobj
8 0 obj
<< /Type /Font
/Subtype /Type1
/Name /F1
/BaseFont /Helvetica
/Encoding /WinAnsiEncoding
>>
endobj
9 0 obj
<< /Type /Page
/MediaBox [0.000 0.000 841.890 595.280]
/Parent 3 0 R
/Contents 10 0 R
>>
endobj
10 0 obj
<<
/Length 6000 >>
stream
0.000 0.000 0.000 rg
0.000 0.000 0.000 RG
0.255 w 0 J [ ] 0 d
BT 34.016 548.810 Td /F1 12.8 Tf [(share their views of Ian. The clear message of the book is that Ian H. Sloan has been a role model in science and life.)] TJ ET
BT 34.016 533.242 Td /F1 12.8 Tf [(Uncertainty Quantification in Computational Science)] TJ ET
BT 328.094 533.242 Td /F1 12.8 Tf [( Sunetra Sarkar 2016-08-19 During the last decade, research in Uncertainty )] TJ ET
BT 34.016 517.675 Td /F1 12.8 Tf [(Quantification \(UC\) has received a tremendous boost, in fluid engineering and coupled structural-fluids systems. New algorithms and )] TJ ET
BT 34.016 502.107 Td /F1 12.8 Tf [(adaptive variants have also emerged. This timely compendium overviews in detail the current state of the art of the field, including )] TJ ET
BT 34.016 486.539 Td /F1 12.8 Tf [(advances in structural engineering, along with the recent focus on fluids and coupled systems. Such a strong compilation of these )] TJ ET
BT 34.016 470.971 Td /F1 12.8 Tf [(vibrant research areas will certainly be an inspirational reference material for the scientific community.)] TJ ET
BT 34.016 455.404 Td /F1 12.8 Tf [(Handbook of Computational Statistics)] TJ ET
BT 246.609 455.404 Td /F1 12.8 Tf [( Yuichi Mori 2004-07-14 The Handbook of Computational Statistics: Concepts and Methodology is )] TJ ET
BT 34.016 439.836 Td /F1 12.8 Tf [(divided into four parts. It begins with an overview over the field of Computational Statistics. The second part presents several topics in )] TJ ET
BT 34.016 424.268 Td /F1 12.8 Tf [(the supporting field of statistical computing. Emphasis is placed on the need of fast and accurate numerical algorithms and it discusses )] TJ ET
BT 34.016 408.700 Td /F1 12.8 Tf [(some of the basic methodologies for transformation, data base handling and graphics treatment. The third part focuses on statistical )] TJ ET
BT 34.016 393.133 Td /F1 12.8 Tf [(methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data. Finally a set )] TJ ET
BT 34.016 377.565 Td /F1 12.8 Tf [(of selected applications like Bioinformatics, Medical Imaging, Finance and Network Intrusion Detection highlight the usefulness of )] TJ ET
BT 34.016 361.997 Td /F1 12.8 Tf [(computational statistics.)] TJ ET
BT 34.016 346.429 Td /F1 12.8 Tf [(Dirichlet and Related Distributions)] TJ ET
BT 226.031 346.429 Td /F1 12.8 Tf [( Kai Wang Ng 2011-05-03 The Dirichlet distribution appears in many areas of application, which )] TJ ET
BT 34.016 330.862 Td /F1 12.8 Tf [(include modelling of compositional data, Bayesian analysis, statistical genetics, and nonparametric inference. This book provides a )] TJ ET
BT 34.016 315.294 Td /F1 12.8 Tf [(comprehensive review of the Dirichlet distribution and two extended versions, the Grouped Dirichlet Distribution \(GDD\) and the Nested )] TJ ET
BT 34.016 299.726 Td /F1 12.8 Tf [(Dirichlet Distribution \(NDD\), arising from likelihood and Bayesian analysis of incomplete categorical data and survey data with non-)] TJ ET
BT 34.016 284.158 Td /F1 12.8 Tf [(response. The theoretical properties and applications are also reviewed in detail for other related distributions, such as the inverted )] TJ ET
BT 34.016 268.591 Td /F1 12.8 Tf [(Dirichlet distribution, Dirichlet-multinomial distribution, the truncated Dirichlet distribution, the generalized Dirichlet distribution, Hyper-)] TJ ET
BT 34.016 253.023 Td /F1 12.8 Tf [(Dirichlet distribution, scaled Dirichlet distribution, mixed Dirichlet distribution, Liouville distribution, and the generalized Liouville )] TJ ET
BT 34.016 237.455 Td /F1 12.8 Tf [(distribution. Key Features: Presents many of the results and applications that are scattered throughout the literature in one single )] TJ ET
BT 34.016 221.887 Td /F1 12.8 Tf [(volume. Looks at the most recent results such as survival function and characteristic function for the uniform distributions over the hyper-)] TJ ET
BT 34.016 206.320 Td /F1 12.8 Tf [(plane and simplex; distribution for linear function of Dirichlet components; estimation via the expectation-maximization gradient algorithm )] TJ ET
BT 34.016 190.752 Td /F1 12.8 Tf [(and application; etc. Likelihood and Bayesian analyses of incomplete categorical data by using GDD, NDD, and the generalized Dirichlet )] TJ ET
BT 34.016 175.184 Td /F1 12.8 Tf [(distribution are illustrated in detail through the EM algorithm and data augmentation structure. Presents a systematic exposition of the )] TJ ET
BT 34.016 159.616 Td /F1 12.8 Tf [(Dirichlet-multinomial distribution for multinomial data with extra variation which cannot be handled by the multinomial distribution. S-)] TJ ET
BT 34.016 144.049 Td /F1 12.8 Tf [(plus/R codes are featured along with practical examples illustrating the methods. Practitioners and researchers working in areas such as )] TJ ET
BT 34.016 128.481 Td /F1 12.8 Tf [(medical science, biological science and social science will benefit from this book.)] TJ ET
BT 34.016 112.913 Td /F1 12.8 Tf [(Statistical Computing with R)] TJ ET
BT 192.728 112.913 Td /F1 12.8 Tf [( Maria L. Rizzo 2007-11-15 Computational statistics and statistical computing are two areas that employ )] TJ ET
BT 34.016 97.345 Td /F1 12.8 Tf [(computational, graphical, and numerical approaches to solve statistical problems, making the versatile R language an ideal computing )] TJ ET
BT 34.016 81.778 Td /F1 12.8 Tf [(environment for these fields. One of the first books on these topics to feature R, Statistical Computing with R covers the traditiona)] TJ ET
BT 34.016 66.210 Td /F1 12.8 Tf [(Monte Carlo and Quasi-Monte Carlo Methods 2000)] TJ ET
BT 323.135 66.210 Td /F1 12.8 Tf [( Kai-Tai Fang 2011-06-28 This book represents the refereed proceedings of the )] TJ ET
BT 34.016 50.642 Td /F1 12.8 Tf [(Fourth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing which was held at Hong Kong )] TJ ET
endstream
endobj
11 0 obj
<< /Type /Page
/MediaBox [0.000 0.000 841.890 595.280]
/Parent 3 0 R
/Contents 12 0 R
>>
endobj
12 0 obj
<<
/Length 5755 >>
stream
0.000 0.000 0.000 rg
0.000 0.000 0.000 RG
0.255 w 0 J [ ] 0 d
BT 34.016 548.810 Td /F1 12.8 Tf [(Baptist University in 2000. An important feature are invited surveys of the state-of-the-art in key areas such as multidimensional )] TJ ET
BT 34.016 533.242 Td /F1 12.8 Tf [(numerical integration, low-discrepancy point sets, random number generation, and applications of Monte Carlo and quasi-Monte Carlo )] TJ ET
BT 34.016 517.675 Td /F1 12.8 Tf [(methods. These proceedings include also carefully selected contributed papers on all aspects of Monte Carlo and quasi-Monte Carlo )] TJ ET
BT 34.016 502.107 Td /F1 12.8 Tf [(methods. The reader will be informed about current research in this very active field.)] TJ ET
BT 34.016 486.539 Td /F1 12.8 Tf [(Approximating Integrals Via Monte Carlo and Deterministic Methods)] TJ ET
0.255 w 0 J [ ] 0 d
34.016 484.435 m 417.357 484.435 l S
BT 417.357 486.539 Td /F1 12.8 Tf [( 2000 )] TJ ET
BT 34.016 470.971 Td /F1 12.8 Tf [(Applications of Discrete-time Markov Chains and Poisson Processes to Air Pollution Modeling and Studies)] TJ ET
BT 632.781 470.971 Td /F1 12.8 Tf [( Eliane Regina Rodrigues )] TJ ET
BT 34.016 455.404 Td /F1 12.8 Tf [(2012-09-02 ?In this brief we consider some stochastic models that may be used to study problems related to environmental matters, in )] TJ ET
BT 34.016 439.836 Td /F1 12.8 Tf [(particular, air pollution. The impact of exposure to air pollutants on people's health is a very clear and well documented subject. )] TJ ET
BT 34.016 424.268 Td /F1 12.8 Tf [(Therefore, it is very important to obtain ways to predict or explain the behaviour of pollutants in general. Depending on the type of )] TJ ET
BT 34.016 408.700 Td /F1 12.8 Tf [(question that one is interested in answering, there are several of ways studying that problem. Among them we may quote, analysis of )] TJ ET
BT 34.016 393.133 Td /F1 12.8 Tf [(the time series of the pollutants' measurements, analysis of the information obtained directly from the data, for instance, daily, weekly or )] TJ ET
BT 34.016 377.565 Td /F1 12.8 Tf [(monthly averages and standard deviations. Another way to study the behaviour of pollutants in general is through mathematical models. )] TJ ET
BT 34.016 361.997 Td /F1 12.8 Tf [(In the mathematical framework we may have for instance deterministic or stochastic models. The type of models that we are going to )] TJ ET
BT 34.016 346.429 Td /F1 12.8 Tf [(consider in this brief are the stochastic ones.?)] TJ ET
BT 34.016 330.862 Td /F1 12.8 Tf [(Stochastic Analysis 2010)] TJ ET
BT 175.745 330.862 Td /F1 12.8 Tf [( Dan Crisan 2010-11-26 Stochastic Analysis aims to provide mathematical tools to describe and model high )] TJ ET
BT 34.016 315.294 Td /F1 12.8 Tf [(dimensional random systems. Such tools arise in the study of Stochastic Differential Equations and Stochastic Partial Differential )] TJ ET
BT 34.016 299.726 Td /F1 12.8 Tf [(Equations, Infinite Dimensional Stochastic Geometry, Random Media and Interacting Particle Systems, Super-processes, Stochastic )] TJ ET
BT 34.016 284.158 Td /F1 12.8 Tf [(Filtering, Mathematical Finance, etc. Stochastic Analysis has emerged as a core area of late 20th century Mathematics and is currently )] TJ ET
BT 34.016 268.591 Td /F1 12.8 Tf [(undergoing a rapid scientific development. The special volume “Stochastic Analysis 2010” provides a sample of the current research in )] TJ ET
BT 34.016 253.023 Td /F1 12.8 Tf [(the different branches of the subject. It includes the collected works of the participants at the Stochastic Analysis section of the 7th )] TJ ET
BT 34.016 237.455 Td /F1 12.8 Tf [(ISAAC Congress organized at Imperial College London in July 2009.)] TJ ET
BT 34.016 221.887 Td /F1 12.8 Tf [(Bayesian Missing Data Problems)] TJ ET
0.255 w 0 J [ ] 0 d
34.016 219.784 m 221.071 219.784 l S
BT 221.071 221.887 Td /F1 12.8 Tf [( Ming T. Tan 2009-08-26 Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative )] TJ ET
BT 34.016 206.320 Td /F1 12.8 Tf [(Computation presents solutions to missing data problems through explicit or noniterative sampling calculation of Bayesian posteriors. )] TJ ET
BT 34.016 190.752 Td /F1 12.8 Tf [(The methods are based on the inverse Bayes formulae discovered by one of the author in 1995. Applying the Bayesian approach to )] TJ ET
BT 34.016 175.184 Td /F1 12.8 Tf [(important real-world problems, the authors focus on exact numerical solutions, a conditional sampling approach via data augmentation, )] TJ ET
BT 34.016 159.616 Td /F1 12.8 Tf [(and a noniterative sampling approach via EM-type algorithms. After introducing the missing data problems, Bayesian approach, and )] TJ ET
BT 34.016 144.049 Td /F1 12.8 Tf [(posterior computation, the book succinctly describes EM-type algorithms, Monte Carlo simulation, numerical techniques, and )] TJ ET
BT 34.016 128.481 Td /F1 12.8 Tf [(optimization methods. It then gives exact posterior solutions for problems, such as nonresponses in surveys and cross-over trials with )] TJ ET
BT 34.016 112.913 Td /F1 12.8 Tf [(missing values. It also provides noniterative posterior sampling solutions for problems, such as contingency tables with supplemental )] TJ ET
BT 34.016 97.345 Td /F1 12.8 Tf [(margins, aggregated responses in surveys, zero-inflated Poisson, capture-recapture models, mixed effects models, right-censored )] TJ ET
BT 34.016 81.778 Td /F1 12.8 Tf [(regression model, and constrained parameter models. The text concludes with a discussion on compatibility, a fundamental issue in )] TJ ET
BT 34.016 66.210 Td /F1 12.8 Tf [(Bayesian inference. This book offers a unified treatment of an array of statistical problems that involve missing data and constrained )] TJ ET
endstream
endobj
13 0 obj
<< /Type /Page
/MediaBox [0.000 0.000 841.890 595.280]
/Parent 3 0 R
/Contents 14 0 R
>>
endobj
14 0 obj
<<
/Length 5958 >>
stream
0.000 0.000 0.000 rg
0.000 0.000 0.000 RG
0.255 w 0 J [ ] 0 d
BT 34.016 548.810 Td /F1 12.8 Tf [(parameters. It shows how Bayesian procedures can be useful in solving these problems.)] TJ ET
BT 34.016 533.242 Td /F1 12.8 Tf [(Computation of Multivariate Normal and t Probabilities)] TJ ET
BT 338.702 533.242 Td /F1 12.8 Tf [( Alan Genz 2009-07-09 Multivariate normal and t probabilities are needed for )] TJ ET
BT 34.016 517.675 Td /F1 12.8 Tf [(statistical inference in many applications. Modern statistical computation packages provide functions for the computation of these )] TJ ET
BT 34.016 502.107 Td /F1 12.8 Tf [(probabilities for problems with one or two variables. This book describes recently developed methods for accurate and efficient )] TJ ET
BT 34.016 486.539 Td /F1 12.8 Tf [(computation of the required probability values for problems with two or more variables. The book discusses methods for specialized )] TJ ET
BT 34.016 470.971 Td /F1 12.8 Tf [(problems as well as methods for general problems. The book includes examples that illustrate the probability computations for a variety )] TJ ET
BT 34.016 455.404 Td /F1 12.8 Tf [(of applications.)] TJ ET
BT 34.016 439.836 Td /F1 12.8 Tf [(Computational Approaches for Aerospace Design)] TJ ET
BT 313.929 439.836 Td /F1 12.8 Tf [( Andy Keane 2005-08-05 Over the last fifty years, the ability to carry out analysis as a )] TJ ET
BT 34.016 424.268 Td /F1 12.8 Tf [(precursor to decision making in engineering design has increased dramatically. In particular, the advent of modern computing systems )] TJ ET
BT 34.016 408.700 Td /F1 12.8 Tf [(and the development of advanced numerical methods have made computational modelling a vital tool for producing optimized designs. )] TJ ET
BT 34.016 393.133 Td /F1 12.8 Tf [(This text explores how computer-aided analysis has revolutionized aerospace engineering, providing a comprehensive coverage of the )] TJ ET
BT 34.016 377.565 Td /F1 12.8 Tf [(latest technologies underpinning advanced computational design. Worked case studies and over 500 references to the primary research )] TJ ET
BT 34.016 361.997 Td /F1 12.8 Tf [(literature allow the reader to gain a full understanding of the technology, giving a valuable insight into the world’s most complex )] TJ ET
BT 34.016 346.429 Td /F1 12.8 Tf [(engineering systems. Key Features: Includes background information on the history of aerospace design and established optimization, )] TJ ET
BT 34.016 330.862 Td /F1 12.8 Tf [(geometrical and mathematical modelling techniques, setting recent engineering developments in a relevant context. Examines the latest )] TJ ET
BT 34.016 315.294 Td /F1 12.8 Tf [(methods such as evolutionary and response surface based optimization, adjoint and numerically differentiated sensitivity codes, )] TJ ET
BT 34.016 299.726 Td /F1 12.8 Tf [(uncertainty analysis, and concurrent systems integration schemes using grid-based computing. Methods are illustrated with real-world )] TJ ET
BT 34.016 284.158 Td /F1 12.8 Tf [(applications of structural statics, dynamics and fluid mechanics to satellite, aircraft and aero-engine design problems. Senior )] TJ ET
BT 34.016 268.591 Td /F1 12.8 Tf [(undergraduate and postgraduate engineering students taking courses in aerospace, vehicle and engine design will find this a valuable )] TJ ET
BT 34.016 253.023 Td /F1 12.8 Tf [(resource. It will also be useful for practising engineers and researchers working on computational approaches to design.)] TJ ET
BT 34.016 237.455 Td /F1 12.8 Tf [(Numerical Methods for Nonlinear Estimating Equations)] TJ ET
0.255 w 0 J [ ] 0 d
34.016 235.351 m 343.662 235.351 l S
BT 343.662 237.455 Td /F1 12.8 Tf [( Christopher G. Small 2003 This text provides a comprehensive study of )] TJ ET
BT 34.016 221.887 Td /F1 12.8 Tf [(nonlinear estimating equations and artificial likelihoods for statistical inference. It contains extensive coverage and comparison of hill )] TJ ET
BT 34.016 206.320 Td /F1 12.8 Tf [(climbing algorithms, which, when started at points of nonconcavity often have very poor convergence properties.)] TJ ET
BT 34.016 190.752 Td /F1 12.8 Tf [(Scientific Computing)] TJ ET
BT 150.219 190.752 Td /F1 12.8 Tf [( Michael T. Heath 2018-11-14 This book differs from traditional numerical analysis texts in that it focuses on the )] TJ ET
BT 34.016 175.184 Td /F1 12.8 Tf [(motivation and ideas behind the algorithms presented rather than on detailed analyses of them. It presents a broad overview of methods )] TJ ET
BT 34.016 159.616 Td /F1 12.8 Tf [(and software for solving mathematical problems arising in computational modeling and data analysis, including proper problem )] TJ ET
BT 34.016 144.049 Td /F1 12.8 Tf [(formulation, selection of effective solution algorithms, and interpretation of results. In the 20 years since its original publication, the )] TJ ET
BT 34.016 128.481 Td /F1 12.8 Tf [(modern, fundamental perspective of this book has aged well, and it continues to be used in the classroom. This Classics edition has )] TJ ET
BT 34.016 112.913 Td /F1 12.8 Tf [(been updated to include pointers to Python software and the Chebfun package, expansions on barycentric formulation for Lagrange )] TJ ET
BT 34.016 97.345 Td /F1 12.8 Tf [(polynomial interpretation and stochastic methods, and the availability of about 100 interactive educational modules that dynamically )] TJ ET
BT 34.016 81.778 Td /F1 12.8 Tf [(illustrate the concepts and algorithms in the book. Scientific Computing: An Introductory Survey, Second Edition is intended as both a )] TJ ET
BT 34.016 66.210 Td /F1 12.8 Tf [(textbook and a reference for computationally oriented disciplines that need to solve mathematical problems.)] TJ ET
BT 34.016 50.642 Td /F1 12.8 Tf [(Approximating Integrals via Monte Carlo and Deterministic Methods)] TJ ET
BT 415.228 50.642 Td /F1 12.8 Tf [( Michael Evans 2000-03-23 This book is designed to introduce )] TJ ET
endstream
endobj
15 0 obj
<< /Type /Page
/MediaBox [0.000 0.000 841.890 595.280]
/Parent 3 0 R
/Contents 16 0 R
>>
endobj
16 0 obj
<<
/Length 5952 >>
stream
0.000 0.000 0.000 rg
0.000 0.000 0.000 RG
0.255 w 0 J [ ] 0 d
BT 34.016 548.810 Td /F1 12.8 Tf [(graduate students and researchers to the primary methods useful for approximating integrals. The emphasis is on those methods that )] TJ ET
BT 34.016 533.242 Td /F1 12.8 Tf [(have been found to be of practical use, and although the focus is on approximating higher- dimensional integrals the lower-dimensional )] TJ ET
BT 34.016 517.675 Td /F1 12.8 Tf [(case is also covered. Included in the book are asymptotic techniques, multiple quadrature and quasi-random techniques as well as a )] TJ ET
BT 34.016 502.107 Td /F1 12.8 Tf [(complete development of Monte Carlo algorithms. For the Monte Carlo section importance sampling methods, variance reduction )] TJ ET
BT 34.016 486.539 Td /F1 12.8 Tf [(techniques and the primary Markov Chain Monte Carlo algorithms are covered. This book brings these various techniques together for )] TJ ET
BT 34.016 470.971 Td /F1 12.8 Tf [(the first time, and hence provides an accessible textbook and reference for researchers in a wide variety of disciplines.)] TJ ET
BT 34.016 455.404 Td /F1 12.8 Tf [(Data Analysis from Statistical Foundations)] TJ ET
BT 272.810 455.404 Td /F1 12.8 Tf [( Donald Alexander Stuart Fraser 2001 Data Analysis from Statistical Foundations)] TJ ET
BT 34.016 439.836 Td /F1 12.8 Tf [(Elements of Distribution Theory)] TJ ET
0.255 w 0 J [ ] 0 d
34.016 437.732 m 211.865 437.732 l S
BT 211.865 439.836 Td /F1 12.8 Tf [( Thomas A. Severini 2005-08-08 This detailed introduction to distribution theory uses no measure theory, )] TJ ET
BT 34.016 424.268 Td /F1 12.8 Tf [(making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds )] TJ ET
BT 34.016 408.700 Td /F1 12.8 Tf [(in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix )] TJ ET
BT 34.016 393.133 Td /F1 12.8 Tf [(gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic )] TJ ET
BT 34.016 377.565 Td /F1 12.8 Tf [(distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the )] TJ ET
BT 34.016 361.997 Td /F1 12.8 Tf [(central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to )] TJ ET
BT 34.016 346.429 Td /F1 12.8 Tf [(integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical )] TJ ET
BT 34.016 330.862 Td /F1 12.8 Tf [(methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered )] TJ ET
BT 34.016 315.294 Td /F1 12.8 Tf [(comprehensively.)] TJ ET
BT 34.016 299.726 Td /F1 12.8 Tf [(Statistics in Action)] TJ ET
BT 137.469 299.726 Td /F1 12.8 Tf [( Jerald F. Lawless 2014-03-03 Commissioned by the Statistical Society of Canada \(SSC\), Statistics in Action: A )] TJ ET
BT 34.016 284.158 Td /F1 12.8 Tf [(Canadian Outlook helps both general readers and users of statistics better appreciate the scope and importance of statistics. It presents )] TJ ET
BT 34.016 268.591 Td /F1 12.8 Tf [(the ways in which statistics is used while highlighting key contributions that Canadian statisticians are making to science, technology, )] TJ ET
BT 34.016 253.023 Td /F1 12.8 Tf [(business, government, and other areas. The book emphasizes the role and impact of computing in statistical modeling and analysis, )] TJ ET
BT 34.016 237.455 Td /F1 12.8 Tf [(including the issues involved with the huge amounts of data being generated by automated processes. The first two chapters review the )] TJ ET
BT 34.016 221.887 Td /F1 12.8 Tf [(development of statistics as a discipline in Canada and describe some major contributions to survey methodology made by Statistics )] TJ ET
BT 34.016 206.320 Td /F1 12.8 Tf [(Canada, one of the world’s premier official statistics agencies. The book next discusses how statistical methodologies, such as )] TJ ET
BT 34.016 190.752 Td /F1 12.8 Tf [(functional data analysis and the Metropolis algorithm, are applied in a wide variety of fields, including risk management and genetics. It )] TJ ET
BT 34.016 175.184 Td /F1 12.8 Tf [(then focuses on the application of statistical methods in medicine and public health as well as finance and e-commerce. The remainder )] TJ ET
BT 34.016 159.616 Td /F1 12.8 Tf [(of the book addresses how statistics is used to study critical scientific areas, including difficult-to-access populations, endangered )] TJ ET
BT 34.016 144.049 Td /F1 12.8 Tf [(species, climate change, and agricultural forecasts. About the SSC Founded in Montréal in 1972, the SSC is the main professional )] TJ ET
BT 34.016 128.481 Td /F1 12.8 Tf [(organization for statisticians and related professionals in Canada. Its mission is to promote the use and development of statistics and )] TJ ET
BT 34.016 112.913 Td /F1 12.8 Tf [(probability. The SSC publishes the bilingual quarterly newsletter SSC Liaison and the peer-reviewed scientific journal The Canadian )] TJ ET
BT 34.016 97.345 Td /F1 12.8 Tf [(Journal of Statistics. More information can be found at www.ssc.ca.)] TJ ET
BT 34.016 81.778 Td /F1 12.8 Tf [(Measurement Error and Misclassification in Statistics and Epidemiology)] TJ ET
BT 437.183 81.778 Td /F1 12.8 Tf [( Paul Gustafson 2003-09-25 Mismeasurement of explanatory )] TJ ET
BT 34.016 66.210 Td /F1 12.8 Tf [(variables is a common hazard when using statistical modeling techniques, and particularly so in fields such as biostatistics and )] TJ ET
BT 34.016 50.642 Td /F1 12.8 Tf [(epidemiology where perceived risk factors cannot always be measured accurately. With this perspective and a focus on both continuous )] TJ ET
endstream
endobj
17 0 obj
<< /Type /Page
/MediaBox [0.000 0.000 841.890 595.280]
/Parent 3 0 R
/Contents 18 0 R
>>
endobj
18 0 obj
<<
/Length 5590 >>
stream
0.000 0.000 0.000 rg
0.000 0.000 0.000 RG
0.255 w 0 J [ ] 0 d
BT 34.016 548.810 Td /F1 12.8 Tf [(and categorical variables, Measurement Error and Misclassi)] TJ ET
BT 34.016 533.242 Td /F1 12.8 Tf [(Bayesian Estimation and Tracking)] TJ ET
BT 226.757 533.242 Td /F1 12.8 Tf [( Anton J. Haug 2012-05-29 A practical approach to estimating and tracking dynamicsystems in real-)] TJ ET
BT 34.016 517.675 Td /F1 12.8 Tf [(worl applications Much of the literature on performing estimation for non-Gaussiansystems is short on practical methodology, while )] TJ ET
BT 34.016 502.107 Td /F1 12.8 Tf [(Gaussian methodsoften lack a cohesive derivation. Bayesian Estimation andTracking addresses the gap in the field on both )] TJ ET
BT 34.016 486.539 Td /F1 12.8 Tf [(accounts,providing readers with a comprehensive overview of methods forestimating both linear and nonlinear dynamic systems driven )] TJ ET
BT 34.016 470.971 Td /F1 12.8 Tf [(byGaussian and non-Gaussian noices. Featuring a unified approach to Bayesian estimation andtracking, the book emphasizes the )] TJ ET
BT 34.016 455.404 Td /F1 12.8 Tf [(derivation of all trackingalgorithms within a Bayesian framework and describes effectivenumerical methods for evaluating density-)] TJ ET
BT 34.016 439.836 Td /F1 12.8 Tf [(weighted integrals,including linear and nonlinear Kalman filters for Gaussian-weightedintegrals and particle filters for non-Gaussian )] TJ ET
BT 34.016 424.268 Td /F1 12.8 Tf [(cases. The authorfirst emphasizes detailed derivations from first principles ofeeach estimation method and goes on to use illustrative )] TJ ET
BT 34.016 408.700 Td /F1 12.8 Tf [(anddetailed step-by-step instructions for each method that makescoding of the tracking filter simple and easy to understand. Case )] TJ ET
BT 34.016 393.133 Td /F1 12.8 Tf [(studies are employed to showcase applications of thediscussed topics. In addition, the book supplies block diagrams foreach algorithm, )] TJ ET
BT 34.016 377.565 Td /F1 12.8 Tf [(allowing readers to develop their own MATLAB®toolbox of estimation methods. Bayesian Estimation and Tracking is an excellent book )] TJ ET
BT 34.016 361.997 Td /F1 12.8 Tf [(forcourses on estimation and tracking methods at the graduate level.The book also serves as a valuable reference for )] TJ ET
BT 34.016 346.429 Td /F1 12.8 Tf [(researchscientists, mathematicians, and engineers seeking a deeperunderstanding of the topics.)] TJ ET
BT 34.016 330.862 Td /F1 12.8 Tf [(Introducing Monte Carlo Methods with R)] TJ ET
BT 261.476 330.862 Td /F1 12.8 Tf [( Christian Robert 2010 This book covers the main tools used in statistical simulation from a )] TJ ET
BT 34.016 315.294 Td /F1 12.8 Tf [(programmer’s point of view, explaining the R implementation of each simulation technique and providing the output for better )] TJ ET
BT 34.016 299.726 Td /F1 12.8 Tf [(understanding and comparison.)] TJ ET
BT 34.016 284.158 Td /F1 12.8 Tf [(Surrogate Model-Based Engineering Design and Optimization)] TJ ET
0.255 w 0 J [ ] 0 d
34.016 282.055 m 382.664 282.055 l S
BT 382.664 284.158 Td /F1 12.8 Tf [( Ping Jiang 2019-11-01 This book covers some of the most popular )] TJ ET
BT 34.016 268.591 Td /F1 12.8 Tf [(methods in design space sampling, ensembling surrogate models, multi-fidelity surrogate model construction, surrogate model selection )] TJ ET
BT 34.016 253.023 Td /F1 12.8 Tf [(and validation, surrogate-based robust design optimization, and surrogate-based evolutionary optimization. Surrogate or metamodels )] TJ ET
BT 34.016 237.455 Td /F1 12.8 Tf [(are now frequently used in complex engineering product design to replace expensive simulations or physical experiments. They are )] TJ ET
BT 34.016 221.887 Td /F1 12.8 Tf [(constructed from available input parameter values and the corresponding output performance or quantities of interest \(QOIs\) to provide )] TJ ET
BT 34.016 206.320 Td /F1 12.8 Tf [(predictions based on the fitted or interpolated mathematical relationships. The book highlights a range of methods for ensembling )] TJ ET
BT 34.016 190.752 Td /F1 12.8 Tf [(surrogate and multi-fidelity models, which offer a good balance between surrogate modeling accuracy and building cost. A number of )] TJ ET
BT 34.016 175.184 Td /F1 12.8 Tf [(real-world engineering design problems, such as three-dimensional aircraft design, are also provided to illustrate the ability of surrogates )] TJ ET
BT 34.016 159.616 Td /F1 12.8 Tf [(for supporting complex engineering design. Lastly, illustrative examples are included throughout to help explain the approaches in a )] TJ ET
BT 34.016 144.049 Td /F1 12.8 Tf [(more “hands-on” manner.)] TJ ET
BT 34.016 128.481 Td /F1 12.8 Tf [(Calibration of Watershed Models)] TJ ET
BT 218.954 128.481 Td /F1 12.8 Tf [( Qingyun Duan 2003-01-10 Published by the American Geophysical Union as part of the Water Science )] TJ ET
BT 34.016 112.913 Td /F1 12.8 Tf [(and Application Series, Volume 6. During the past four decades, computer-based mathematical models of watershed hydrology have )] TJ ET
BT 34.016 97.345 Td /F1 12.8 Tf [(been widely used for a variety of applications including hydrologic forecasting, hydrologic design, and water resources management. )] TJ ET
BT 34.016 81.778 Td /F1 12.8 Tf [(These models are based on general mathematical descriptions of the watershed processes that transform natural forcing \(e.g., rainfall )] TJ ET
BT 34.016 66.210 Td /F1 12.8 Tf [(over the landscape\) into response \(e.g., runoff in the rivers\). The user of a watershed hydrology model must specify the model )] TJ ET
endstream
endobj
19 0 obj
<< /Type /Page
/MediaBox [0.000 0.000 841.890 595.280]
/Parent 3 0 R
/Contents 20 0 R
>>
endobj
20 0 obj
<<
/Length 5937 >>
stream
0.000 0.000 0.000 rg
0.000 0.000 0.000 RG
0.255 w 0 J [ ] 0 d
BT 34.016 548.810 Td /F1 12.8 Tf [(parameters before the model is able to properly simulate the watershed behavior.)] TJ ET
BT 34.016 533.242 Td /F1 12.8 Tf [(Biometrics - Volume II)] TJ ET
0.255 w 0 J [ ] 0 d
34.016 531.139 m 158.711 531.139 l S
BT 158.711 533.242 Td /F1 12.8 Tf [( Susan R. Wilson 2009-02-18 Biometrics is a component of Encyclopedia of Mathematical Sciences in the global )] TJ ET
BT 34.016 517.675 Td /F1 12.8 Tf [(Encyclopedia of Life Support Systems \(EOLSS\), which is an integrated compendium of twenty one Encyclopedias. Biometry is a broad )] TJ ET
BT 34.016 502.107 Td /F1 12.8 Tf [(discipline covering all applications of statistics and mathematics to biology. The Theme Biometrics is divided into areas of expertise )] TJ ET
BT 34.016 486.539 Td /F1 12.8 Tf [(essential for a proper application of statistical and mathematical methods to contemporary biological problems. These volumes cover )] TJ ET
BT 34.016 470.971 Td /F1 12.8 Tf [(four main topics: Data Collection and Analysis, Statistical Methodology, Computation, Biostatistical Methods and Research Design and )] TJ ET
BT 34.016 455.404 Td /F1 12.8 Tf [(Selected Topics. These volumes are aimed at the following five major target audiences: University and College students Educators, )] TJ ET
BT 34.016 439.836 Td /F1 12.8 Tf [(Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.)] TJ ET
BT 34.016 424.268 Td /F1 12.8 Tf [(Generalized Latent Variable Modeling)] TJ ET
BT 247.323 424.268 Td /F1 12.8 Tf [( Anders Skrondal 2004-05-11 This book unifies and extends latent variable models, including )] TJ ET
BT 34.016 408.700 Td /F1 12.8 Tf [(multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture )] TJ ET
BT 34.016 393.133 Td /F1 12.8 Tf [(models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and )] TJ ET
BT 34.016 377.565 Td /F1 12.8 Tf [(contrast a wi)] TJ ET
BT 34.016 361.997 Td /F1 12.8 Tf [(Intelligent Control Systems Using Computational Intelligence Techniques)] TJ ET
BT 445.012 361.997 Td /F1 12.8 Tf [( A.E. Ruano 2005-07-18 Intelligent Control techniques are )] TJ ET
BT 34.016 346.429 Td /F1 12.8 Tf [(becoming important tools in both academia and industry. Methodologies developed in the field of soft-computing, such as neural )] TJ ET
BT 34.016 330.862 Td /F1 12.8 Tf [(networks, fuzzy systems and evolutionary computation, can lead to accommodation of more complex processes, improved performance )] TJ ET
BT 34.016 315.294 Td /F1 12.8 Tf [(and considerable time savings and cost reductions. Intelligent Control Systems using Computational Intellingence Techniques details the )] TJ ET
BT 34.016 299.726 Td /F1 12.8 Tf [(application of these tools to the field of control systems. Each chapter gives and overview of current approaches in the topic covered, )] TJ ET
BT 34.016 284.158 Td /F1 12.8 Tf [(with a set of the most important references in the field, and then details the author's approach, examining both the theory and practical )] TJ ET
BT 34.016 268.591 Td /F1 12.8 Tf [(applications.)] TJ ET
BT 34.016 253.023 Td /F1 12.8 Tf [(Monte Carlo Methods for Applied Scientists)] TJ ET
BT 278.484 253.023 Td /F1 12.8 Tf [( Ivan Dimov 2008 The Monte Carlo method is inherently parallel and the extensive and rapid )] TJ ET
BT 34.016 237.455 Td /F1 12.8 Tf [(development in parallel computers, computational clusters and grids has resulted in renewed and increasing interest in this method. At )] TJ ET
BT 34.016 221.887 Td /F1 12.8 Tf [(the same time there has been an expansion in the application areas and the method is now widely used in many important areas of )] TJ ET
BT 34.016 206.320 Td /F1 12.8 Tf [(science including nuclear and semiconductor physics, statistical mechanics and heat and mass transfer. This book attempts to bridge )] TJ ET
BT 34.016 190.752 Td /F1 12.8 Tf [(the gap between theory and practice concentrating on modern algorithmic implementation on parallel architecture machines. Although a )] TJ ET
BT 34.016 175.184 Td /F1 12.8 Tf [(suitable text for final year postgraduate mathematicians and computational scientists it is principally aimed at the applied scientists: only )] TJ ET
BT 34.016 159.616 Td /F1 12.8 Tf [(a small amount of mathematical knowledge is assumed and theorem proving is kept to a minimum, with the main focus being on parallel )] TJ ET
BT 34.016 144.049 Td /F1 12.8 Tf [(algorithms development often to applied industrial problems. A selection of algorithms developed both for serial and parallel machines )] TJ ET
BT 34.016 128.481 Td /F1 12.8 Tf [(are provided. Sample Chapter\(s\). Chapter 1: Introduction \(231 KB\). Contents: Basic Results of Monte Carlo Integration; Optimal Monte )] TJ ET
BT 34.016 112.913 Td /F1 12.8 Tf [(Carlo Method for Multidimensional Integrals of Smooth Functions; Iterative Monte Carlo Methods for Linear Equations; Markov Chain )] TJ ET
BT 34.016 97.345 Td /F1 12.8 Tf [(Monte Carlo Methods for Eigenvalue Problems; Monte Carlo Methods for Boundary-Value Problems \(BVP\); Superconvergent Monte )] TJ ET
BT 34.016 81.778 Td /F1 12.8 Tf [(Carlo for Density Function Simulation by B-Splines; Solving Non-Linear Equations; Algorithmic Effciency for Different Computer Models; )] TJ ET
BT 34.016 66.210 Td /F1 12.8 Tf [(Applications for Transport Modeling in Semiconductors and Nanowires. Readership: Applied scientists and mathematicians.)] TJ ET
BT 34.016 50.642 Td /F1 12.8 Tf [(Current Air Quality Issues)] TJ ET
0.255 w 0 J [ ] 0 d
34.016 48.538 m 179.264 48.538 l S
BT 179.264 50.642 Td /F1 12.8 Tf [( Farhad Nejadkoorki 2015-10-21 Air pollution is thus far one of the key environmental issues in urban areas. )] TJ ET
endstream
endobj
21 0 obj
<< /Type /Page
/MediaBox [0.000 0.000 841.890 595.280]
/Parent 3 0 R
/Contents 22 0 R
>>
endobj
22 0 obj
<<
/Length 5922 >>
stream
0.000 0.000 0.000 rg
0.000 0.000 0.000 RG
0.255 w 0 J [ ] 0 d
BT 34.016 548.810 Td /F1 12.8 Tf [(Comprehensive air quality plans are required to manage air pollution for a particular area. Consequently, air should be continuously )] TJ ET
BT 34.016 533.242 Td /F1 12.8 Tf [(sampled, monitored, and modeled to examine different action plans. Reviews and research papers describe air pollution in five main )] TJ ET
BT 34.016 517.675 Td /F1 12.8 Tf [(contexts: Monitoring, Modeling, Risk Assessment, Health, and Indoor Air Pollution. The book is recommended to experts interested in )] TJ ET
BT 34.016 502.107 Td /F1 12.8 Tf [(health and air pollution issues.)] TJ ET
BT 34.016 486.539 Td /F1 12.8 Tf [(Monte Carlo Methods and Models in Finance and Insurance)] TJ ET
0.255 w 0 J [ ] 0 d
34.016 484.435 m 372.044 484.435 l S
BT 372.044 486.539 Td /F1 12.8 Tf [( Ralf Korn 2010-02-26 Offering a unique balance between applications and )] TJ ET
BT 34.016 470.971 Td /F1 12.8 Tf [(calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and )] TJ ET
BT 34.016 455.404 Td /F1 12.8 Tf [(insurance with the theory and applications of Monte Carlo methods. It presents recent methods and algorithms, including the multilevel )] TJ ET
BT 34.016 439.836 Td /F1 12.8 Tf [(Monte Carlo method, the statistical Romberg method, and the Heath–Platen estimator, as well as recent financial and actuarial models, )] TJ ET
BT 34.016 424.268 Td /F1 12.8 Tf [(such as the Cheyette and dynamic mortality models. The authors separately discuss Monte Carlo techniques, stochastic process basics, )] TJ ET
BT 34.016 408.700 Td /F1 12.8 Tf [(and the theoretical background and intuition behind financial and actuarial mathematics, before bringing the topics together to apply the )] TJ ET
BT 34.016 393.133 Td /F1 12.8 Tf [(Monte Carlo methods to areas of finance and insurance. This allows for the easy identification of standard Monte Carlo tools and for a )] TJ ET
BT 34.016 377.565 Td /F1 12.8 Tf [(detailed focus on the main principles of financial and insurance mathematics. The book describes high-level Monte Carlo methods for )] TJ ET
BT 34.016 361.997 Td /F1 12.8 Tf [(standard simulation and the simulation of stochastic processes with continuous and discontinuous paths. It also covers a wide selection )] TJ ET
BT 34.016 346.429 Td /F1 12.8 Tf [(of popular models in finance and insurance, from Black–Scholes to stochastic volatility to interest rate to dynamic mortality. Through its )] TJ ET
BT 34.016 330.862 Td /F1 12.8 Tf [(many numerical and graphical illustrations and simple, insightful examples, this book provides a deep understanding of the scope of )] TJ ET
BT 34.016 315.294 Td /F1 12.8 Tf [(Monte Carlo methods and their use in various financial situations. The intuitive presentation encourages readers to implement and )] TJ ET
BT 34.016 299.726 Td /F1 12.8 Tf [(further develop the simulation methods.)] TJ ET
BT 34.016 284.158 Td /F1 12.8 Tf [(Integrated Tracking, Classification, and Sensor Management)] TJ ET
BT 376.289 284.158 Td /F1 12.8 Tf [( Mahendra Mallick 2012-12-03 A unique guide to the state of the art of )] TJ ET
BT 34.016 268.591 Td /F1 12.8 Tf [(tracking, classification, and sensor management This book addresses the tremendous progress made over the last few decades in )] TJ ET
BT 34.016 253.023 Td /F1 12.8 Tf [(algorithm development and mathematical analysis for filtering, multi-target multi-sensor tracking, sensor management and control, and )] TJ ET
BT 34.016 237.455 Td /F1 12.8 Tf [(target classification. It provides for the first time an integrated treatment of these advanced topics, complete with careful mathematical )] TJ ET
BT 34.016 221.887 Td /F1 12.8 Tf [(formulation, clear description of the theory, and real-world applications. Written by experts in the field, Integrated Tracking, Classification, )] TJ ET
BT 34.016 206.320 Td /F1 12.8 Tf [(and Sensor Management provides readers with easy access to key Bayesian modeling and filtering methods, multi-target tracking )] TJ ET
BT 34.016 190.752 Td /F1 12.8 Tf [(approaches, target classification procedures, and large scale sensor management problem-solving techniques. Features include: An )] TJ ET
BT 34.016 175.184 Td /F1 12.8 Tf [(accessible coverage of random finite set based multi-target filtering algorithms such as the Probability Hypothesis Density filters and )] TJ ET
BT 34.016 159.616 Td /F1 12.8 Tf [(multi-Bernoulli filters with focus on problem solving A succinct overview of the track-oriented MHT that comprehensively collates all )] TJ ET
BT 34.016 144.049 Td /F1 12.8 Tf [(significant developments in filtering and tracking A state-of-the-art algorithm for hybrid Bayesian network \(BN\) inference that is efficient )] TJ ET
BT 34.016 128.481 Td /F1 12.8 Tf [(and scalable for complex classification models New structural results in stochastic sensor scheduling and algorithms for dynamic sensor )] TJ ET
BT 34.016 112.913 Td /F1 12.8 Tf [(scheduling and management Coverage of the posterior Cramer-Rao lower bound \(PCRLB\) for target tracking and sensor management )] TJ ET
BT 34.016 97.345 Td /F1 12.8 Tf [(Insight into cutting-edge military and civilian applications, including intelligence, surveillance, and reconnaissance \(ISR\) With its )] TJ ET
BT 34.016 81.778 Td /F1 12.8 Tf [(emphasis on the latest research results, Integrated Tracking, Classification, and Sensor Management is an invaluable guide for )] TJ ET
BT 34.016 66.210 Td /F1 12.8 Tf [(researchers and practitioners in statistical signal processing, radar systems, operations research, and control theory.)] TJ ET
BT 34.016 50.642 Td /F1 12.8 Tf [(Towards Dependable Robotic Perception)] TJ ET
BT 266.448 50.642 Td /F1 12.8 Tf [( Anna V. Petrovskaya 2011 Reliable perception is required in order for robots to operate safely )] TJ ET
endstream
endobj
23 0 obj
<< /Type /Page
/MediaBox [0.000 0.000 841.890 595.280]
/Parent 3 0 R
/Contents 24 0 R
>>
endobj
24 0 obj
<<
/Length 5988 >>
stream
0.000 0.000 0.000 rg
0.000 0.000 0.000 RG
0.255 w 0 J [ ] 0 d
BT 34.016 548.810 Td /F1 12.8 Tf [(in unpredictable and complex human environments. However, reliability of perceptual inference algorithms has been poorly studied so )] TJ ET
BT 34.016 533.242 Td /F1 12.8 Tf [(far. These algorithms capture uncertain knowledge about the world in the form of probabilistic belief distributions. A number of Monte )] TJ ET
BT 34.016 517.675 Td /F1 12.8 Tf [(Carlo and deterministic approaches have been developed, but their efficiency depends on the degree of smoothness of the beliefs. In )] TJ ET
BT 34.016 502.107 Td /F1 12.8 Tf [(the real world, the smoothness assumption often fails, leading to unreliable perceptual inference results. Motivated by concrete robotics )] TJ ET
BT 34.016 486.539 Td /F1 12.8 Tf [(problems, we propose two novel perceptual inference algorithms that explicitly consider local non-smoothness of beliefs and adapt to it. )] TJ ET
BT 34.016 470.971 Td /F1 12.8 Tf [(Both of these algorithms fall into the category of iterative divide-and-conquer methods and hence scale logarithmically with desired )] TJ ET
BT 34.016 455.404 Td /F1 12.8 Tf [(accuracy. The first algorithm is termed Scaling Series. It is an iterative Monte Carlo technique coupled with annealing. Local non-)] TJ ET
BT 34.016 439.836 Td /F1 12.8 Tf [(smoothness is accounted for by sampling strategy and by annealing schedule. The second algorithm is termed GRAB, which stands for )] TJ ET
BT 34.016 424.268 Td /F1 12.8 Tf [(Guaranteed Recursive Adaptive Bounding. GRAB is an iterative adaptive grid algorithm, which relies on bounds. In this case, local non-)] TJ ET
BT 34.016 408.700 Td /F1 12.8 Tf [(smoothness is captured in terms of local bounds and grid resolution. Scaling Series works well for beliefs with sharp transitions, but )] TJ ET
BT 34.016 393.133 Td /F1 12.8 Tf [(without many discontinuities. GRAB is most appropriate for beliefs with many discontinuities. Both of these algorithms far outperform the )] TJ ET
BT 34.016 377.565 Td /F1 12.8 Tf [(prior art in terms of reliability, efficiency, and accuracy. GRAB is also able to guarantee that a quality approximation of the belief is )] TJ ET
BT 34.016 361.997 Td /F1 12.8 Tf [(produced. The proposed algorithms are evaluated on a diverse set of real robotics problems: tactile perception, autonomous driving, and )] TJ ET
BT 34.016 346.429 Td /F1 12.8 Tf [(mobile manipulation. In tactile perception, we localize objects in 3D starting with very high initial uncertainty and estimating all 6 degrees )] TJ ET
BT 34.016 330.862 Td /F1 12.8 Tf [(of freedom. The localization is performed based on tactile sensory data. Using Scaling Series, we obtain highly accurate and reliable )] TJ ET
BT 34.016 315.294 Td /F1 12.8 Tf [(results in under 1 second. Improved tactile object localization contributes to manufacturing applications, where tactile perception is )] TJ ET
BT 34.016 299.726 Td /F1 12.8 Tf [(widely used for workpiece localization. It also enables robotic applications in situations where vision can be obstructed, such as rescue )] TJ ET
BT 34.016 284.158 Td /F1 12.8 Tf [(robotics and underwater robotics. In autonomous driving, we detect and track vehicles in the vicinity of the robot based on 2D and 3D )] TJ ET
BT 34.016 268.591 Td /F1 12.8 Tf [(laser range finders. In addition to estimating position and velocity of vehicles, we also model and estimate their geometric shape. The )] TJ ET
BT 34.016 253.023 Td /F1 12.8 Tf [(geometric model leads to highly accurate estimates of pose and velocity for each vehicle. It also greatly simplifies association of data, )] TJ ET
BT 34.016 237.455 Td /F1 12.8 Tf [(which are often split up into separate clusters due to occlusion. The proposed Scaling Series algorithm greatly improves reliability and )] TJ ET
BT 34.016 221.887 Td /F1 12.8 Tf [(ensures that the problem is solved within tight real time constraints of autonomous driving. In mobile manipulation, we achieve highly )] TJ ET
BT 34.016 206.320 Td /F1 12.8 Tf [(accurate robot localization based on commonly used 2D laser range finders using the GRAB algorithm. We show that the high accuracy )] TJ ET
BT 34.016 190.752 Td /F1 12.8 Tf [(allows robots to navigate in tight spaces and manipulate objects without having to sense them directly. We demonstrate our approach on )] TJ ET
BT 34.016 175.184 Td /F1 12.8 Tf [(the example of simultaneous building navigation, door handle manipulation, and door opening. We also propose hybrid environment )] TJ ET
BT 34.016 159.616 Td /F1 12.8 Tf [(models, which combine high resolution polygons for objects of interest with low resolution occupancy grid representations for the rest of )] TJ ET
BT 34.016 144.049 Td /F1 12.8 Tf [(the environment. High accuracy indoor localization contributes directly to home/office mobile robotics as well as to future robotics )] TJ ET
BT 34.016 128.481 Td /F1 12.8 Tf [(applications in construction, inspection, and maintenance of buildings. Based on the success of the proposed perceptual inference )] TJ ET
BT 34.016 112.913 Td /F1 12.8 Tf [(algorithms in the concrete robotics problems, it is our hope that this thesis will serve as a starting point for further development of highly )] TJ ET
BT 34.016 97.345 Td /F1 12.8 Tf [(reliable perceptual inference methods.)] TJ ET
BT 34.016 81.778 Td /F1 12.8 Tf [(Inference in Hidden Markov Models)] TJ ET
0.255 w 0 J [ ] 0 d
34.016 79.674 m 234.548 79.674 l S
BT 234.548 81.778 Td /F1 12.8 Tf [( Olivier Cappé 2006-04-18 This book is a comprehensive treatment of inference for hidden Markov )] TJ ET
BT 34.016 66.210 Td /F1 12.8 Tf [(models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to )] TJ ET
BT 34.016 50.642 Td /F1 12.8 Tf [(parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with )] TJ ET
endstream
endobj
25 0 obj
<< /Type /Page
/MediaBox [0.000 0.000 841.890 595.280]
/Parent 3 0 R
/Contents 26 0 R
>>
endobj
26 0 obj
<<
/Length 5813 >>
stream
0.000 0.000 0.000 rg
0.000 0.000 0.000 RG
0.255 w 0 J [ ] 0 d
BT 34.016 548.810 Td /F1 12.8 Tf [(finite state spaces and models with continuous state spaces \(also called state-space models\) requiring approximate simulation-based )] TJ ET
BT 34.016 533.242 Td /F1 12.8 Tf [(algorithms that are also described in detail. Many examples illustrate the algorithms and theory. This book builds on recent )] TJ ET
BT 34.016 517.675 Td /F1 12.8 Tf [(developments to present a self-contained view.)] TJ ET
BT 34.016 502.107 Td /F1 12.8 Tf [(Handbook of Computational Statistics)] TJ ET
BT 246.609 502.107 Td /F1 12.8 Tf [( James E. Gentle 2012-07-06 The Handbook of Computational Statistics - Concepts and Methods )] TJ ET
BT 34.016 486.539 Td /F1 12.8 Tf [(\(second edition\) is a revision of the first edition published in 2004, and contains additional comments and updated information on the )] TJ ET
BT 34.016 470.971 Td /F1 12.8 Tf [(existing chapters, as well as three new chapters addressing recent work in the field of computational statistics. This new edition is )] TJ ET
BT 34.016 455.404 Td /F1 12.8 Tf [(divided into 4 parts in the same way as the first edition. It begins with "How Computational Statistics became the backbone of modern )] TJ ET
BT 34.016 439.836 Td /F1 12.8 Tf [(data science" \(Ch.1\): an overview of the field of Computational Statistics, how it emerged as a separate discipline, and how its own )] TJ ET
BT 34.016 424.268 Td /F1 12.8 Tf [(development mirrored that of hardware and software, including a discussion of current active research. The second part \(Chs. 2 - 15\) )] TJ ET
BT 34.016 408.700 Td /F1 12.8 Tf [(presents several topics in the supporting field of statistical computing. Emphasis is placed on the need for fast and accurate numerical )] TJ ET
BT 34.016 393.133 Td /F1 12.8 Tf [(algorithms, and some of the basic methodologies for transformation, database handling, high-dimensional data and graphics treatment )] TJ ET
BT 34.016 377.565 Td /F1 12.8 Tf [(are discussed. The third part \(Chs. 16 - 33\) focuses on statistical methodology. Special attention is given to smoothing, iterative )] TJ ET
BT 34.016 361.997 Td /F1 12.8 Tf [(procedures, simulation and visualization of multivariate data. Lastly, a set of selected applications \(Chs. 34 - 38\) like Bioinformatics, )] TJ ET
BT 34.016 346.429 Td /F1 12.8 Tf [(Medical Imaging, Finance, Econometrics and Network Intrusion Detection highlight the usefulness of computational statistics in real-)] TJ ET
BT 34.016 330.862 Td /F1 12.8 Tf [(world applications.)] TJ ET
BT 34.016 315.294 Td /F1 12.8 Tf [(Monte Carlo Methods and Applications)] TJ ET
BT 252.984 315.294 Td /F1 12.8 Tf [( Ivan Dimov 2013-01-01 This is the proceedings of the "8th IMACS Seminar on Monte Carlo )] TJ ET
BT 34.016 299.726 Td /F1 12.8 Tf [(Methods" held from August 29 to September 2, 2011 in Borovets, Bulgaria, and organized by the Institute of Information and )] TJ ET
BT 34.016 284.158 Td /F1 12.8 Tf [(Communication Technologies of the Bulgarian Academy of Sciences in cooperation with the International Association for Mathematics )] TJ ET
BT 34.016 268.591 Td /F1 12.8 Tf [(and Computers in Simulation \(IMACS\). Included are 24 papers which cover all topics presented in the sessions of the seminar: )] TJ ET
BT 34.016 253.023 Td /F1 12.8 Tf [(stochastic computation and complexity of high dimensional problems, sensitivity analysis, high-performance computations for Monte )] TJ ET
BT 34.016 237.455 Td /F1 12.8 Tf [(Carlo applications, stochastic metaheuristics for optimization problems, sequential Monte Carlo methods for large-scale problems, )] TJ ET
BT 34.016 221.887 Td /F1 12.8 Tf [(semiconductor devices and nanostructures.)] TJ ET
BT 34.016 206.320 Td /F1 12.8 Tf [(Monte Carlo and Quasi-Monte Carlo Methods 2012)] TJ ET
0.255 w 0 J [ ] 0 d
34.016 204.216 m 323.135 204.216 l S
BT 323.135 206.320 Td /F1 12.8 Tf [( Josef Dick 2013-12-05 This book represents the refereed proceedings of the Tenth )] TJ ET
BT 34.016 190.752 Td /F1 12.8 Tf [(International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of New )] TJ ET
BT 34.016 175.184 Td /F1 12.8 Tf [(South Wales \(Australia\) in February 2012. These biennial conferences are major events for Monte Carlo and the premiere event for )] TJ ET
BT 34.016 159.616 Td /F1 12.8 Tf [(quasi-Monte Carlo research. The proceedings include articles based on invited lectures as well as carefully selected contributed papers )] TJ ET
BT 34.016 144.049 Td /F1 12.8 Tf [(on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. The reader will be provided with information )] TJ ET
BT 34.016 128.481 Td /F1 12.8 Tf [(on latest developments in these very active areas. The book is an excellent reference for theoreticians and practitioners interested in )] TJ ET
BT 34.016 112.913 Td /F1 12.8 Tf [(solving high-dimensional computational problems arising, in particular, in finance, statistics and computer graphics.)] TJ ET
BT 34.016 97.345 Td /F1 12.8 Tf [(Multistability in Physical and Living Systems)] TJ ET
BT 282.003 97.345 Td /F1 12.8 Tf [( Alexander N. Pisarchik )] TJ ET
BT 34.016 81.778 Td /F1 12.8 Tf [(Computational Statistics)] TJ ET
BT 170.772 81.778 Td /F1 12.8 Tf [( Geof H. Givens 2012-11-06 This new edition continues to serve as a comprehensive guide to modern and )] TJ ET
BT 34.016 66.210 Td /F1 12.8 Tf [(classical methods of statistical computing. The book is comprised of four main parts spanning the field: Optimization Integration and )] TJ ET
BT 34.016 50.642 Td /F1 12.8 Tf [(Simulation Bootstrapping Density Estimation and Smoothing Within these sections,each chapter includes a comprehensive introduction )] TJ ET
endstream
endobj
27 0 obj
<< /Type /Page
/MediaBox [0.000 0.000 841.890 595.280]
/Parent 3 0 R
/Annots [ 29 0 R ]
/Contents 28 0 R
>>
endobj
28 0 obj
<<
/Length 3678 >>
stream
0.000 0.000 0.000 rg
0.000 0.000 0.000 RG
0.255 w 0 J [ ] 0 d
BT 34.016 548.810 Td /F1 12.8 Tf [(and step-by-step implementation summaries to accompany the explanations of key methods. The new edition includes updated )] TJ ET
BT 34.016 533.242 Td /F1 12.8 Tf [(coverage and existing topics as well as new topics such as adaptive MCMC and bootstrapping for correlated data. The book website )] TJ ET
BT 34.016 517.675 Td /F1 12.8 Tf [(now includes comprehensive R code for the entire book. There are extensive exercises, real examples, and helpful insights about how to )] TJ ET
BT 34.016 502.107 Td /F1 12.8 Tf [(use the methods in practice.)] TJ ET
BT 34.016 486.539 Td /F1 12.8 Tf [(Random Number Generation and Monte Carlo Methods)] TJ ET
BT 347.933 486.539 Td /F1 12.8 Tf [( James E. Gentle 2006-04-18 Monte Carlo simulation has become one of the )] TJ ET
BT 34.016 470.971 Td /F1 12.8 Tf [(most important tools in all fields of science. Simulation methodology relies on a good source of numbers that appear to be random. )] TJ ET
BT 34.016 455.404 Td /F1 12.8 Tf [(These "pseudorandom" numbers must pass statistical tests just as random samples would. Methods for producing pseudorandom )] TJ ET
BT 34.016 439.836 Td /F1 12.8 Tf [(numbers and transforming those numbers to simulate samples from various distributions are among the most important topics in )] TJ ET
BT 34.016 424.268 Td /F1 12.8 Tf [(statistical computing. This book surveys techniques of random number generation and the use of random numbers in Monte Carlo )] TJ ET
BT 34.016 408.700 Td /F1 12.8 Tf [(simulation. The book covers basic principles, as well as newer methods such as parallel random number generation, nonlinear )] TJ ET
BT 34.016 393.133 Td /F1 12.8 Tf [(congruential generators, quasi Monte Carlo methods, and Markov chain Monte Carlo. The best methods for generating random variates )] TJ ET
BT 34.016 377.565 Td /F1 12.8 Tf [(from the standard distributions are presented, but also general techniques useful in more complicated models and in novel settings are )] TJ ET
BT 34.016 361.997 Td /F1 12.8 Tf [(described. The emphasis throughout the book is on practical methods that work well in current computing environments. The book )] TJ ET
BT 34.016 346.429 Td /F1 12.8 Tf [(includes exercises and can be used as a test or supplementary text for various courses in modern statistics. It could serve as the )] TJ ET
BT 34.016 330.862 Td /F1 12.8 Tf [(primary test for a specialized course in statistical computing, or as a supplementary text for a course in computational statistics and other )] TJ ET
BT 34.016 315.294 Td /F1 12.8 Tf [(areas of modern statistics that rely on simulation. The book, which covers recent developments in the field, could also serve as a useful )] TJ ET
BT 34.016 299.726 Td /F1 12.8 Tf [(reference for practitioners. Although some familiarity with probability and statistics is assumed, the book is accessible to a broad )] TJ ET
BT 34.016 284.158 Td /F1 12.8 Tf [(audience. The second edition is approximately 50% longer than the first edition. It includes advances in methods for parallel random )] TJ ET
BT 34.016 268.591 Td /F1 12.8 Tf [(number generation, universal methods for generation of nonuniform variates, perfect sampling, and software for random number )] TJ ET
BT 34.016 253.023 Td /F1 12.8 Tf [(generation.)] TJ ET
BT 36.266 211.795 Td /F1 8.0 Tf [(approximating-integrals-via-monte-carlo-and-deterministic-methods)] TJ ET
BT 581.952 212.002 Td /F1 8.0 Tf [(Downloaded from )] TJ ET
BT 646.864 211.795 Td /F1 8.0 Tf [(blog.payboy.biz)] TJ ET
BT 702.448 212.002 Td /F1 8.0 Tf [( on October 7, 2022 by guest)] TJ ET
endstream
endobj
29 0 obj
<< /Type /Annot
/Subtype /Link
/A 30 0 R
/Border [0 0 0]
/H /I
/Rect [ 646.8643 211.0549 702.4483 219.1949 ]
>>
endobj
30 0 obj
<< /Type /Action
/S /URI
/URI (https://blog.payboy.biz)
>>
endobj
xref
0 31
0000000000 65535 f
0000000009 00000 n
0000000074 00000 n
0000000120 00000 n
0000000344 00000 n
0000000373 00000 n
0000000817 00000 n
0000000920 00000 n
0000005509 00000 n
0000005616 00000 n
0000005720 00000 n
0000011773 00000 n
0000011878 00000 n
0000017686 00000 n
0000017791 00000 n
0000023802 00000 n
0000023907 00000 n
0000029912 00000 n
0000030017 00000 n
0000035660 00000 n
0000035765 00000 n
0000041755 00000 n
0000041860 00000 n
0000047835 00000 n
0000047940 00000 n
0000053981 00000 n
0000054086 00000 n
0000059952 00000 n
0000060076 00000 n
0000063807 00000 n
0000063935 00000 n
trailer
<<
/Size 31
/Root 1 0 R
/Info 5 0 R
>>
startxref
64010
%%EOF