Journal of Statistical Computation and Simulation PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Journal of Statistical Computation and Simulation PDF full book. Access full book title Journal of Statistical Computation and Simulation by . Download full books in PDF and EPUB format.

Journal of Statistical Computation and Simulation

Journal of Statistical Computation and Simulation PDF Author:
Publisher:
ISBN:
Category : Digital computer simulation
Languages : en
Pages : 278

Book Description

Journal of Statistical Computation and Simulation

Journal of Statistical Computation and Simulation PDF Author:
Publisher:
ISBN:
Category : Digital computer simulation
Languages : en
Pages : 278
Book Description


Monte-Carlo Simulation-Based Statistical Modeling

Monte-Carlo Simulation-Based Statistical Modeling PDF Author: Ding-Geng (Din) Chen
Publisher: Springer
ISBN: 9811033072
Category : Medical
Languages : en
Pages : 430
Book Description
This book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications. It is divided into three parts, with the first providing an overview of Monte-Carlo techniques, the second focusing on missing data Monte-Carlo methods, and the third addressing Bayesian and general statistical modeling using Monte-Carlo simulations. The data and computer programs used here will also be made publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, and to readily apply them in their own research. Featuring highly topical content, the book has the potential to impact model development and data analyses across a wide spectrum of fields, and to spark further research in this direction.

The Frontiers of Statistical Computation, Simulation & Modeling

The Frontiers of Statistical Computation, Simulation & Modeling PDF Author: Peter R. Nelson
Publisher: Amer Sciences Press
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 364
Book Description


Critical Rationalism, Metaphysics and Science

Critical Rationalism, Metaphysics and Science PDF Author: I.C. Jarvie
Publisher: Springer Science & Business Media
ISBN: 9401104719
Category : Philosophy
Languages : en
Pages : 266
Book Description
I suppose Joseph Agassi's best and dearest self-description, his cher ished wish, is to practice what his 1988 book promises: The Gentle Art of Philosophical Polemics. But for me, and for so many who know him, our Agassi is tough-minded, not tender, not so gentle. True to his beloved critical thinking, he is ever the falsificationist, testing himself of course as much as everyone else. How, he asks himself, can he engage others in their own self-critical exploration? Irritate? Question their logic, their facts, their presuppositions, their rationales? Subvert their reasoning, uncover their motives? Help them to lose their balance, but always help them, make them do it to, and for, themselves. Out of their own mouths, and minds, and imagination. A unique teacher, in classroom and out; not for everyone. Agassi is not quite a tight textual Talmudist disputant, not quite the competitor in the marketplace of ideas offered for persuasive sale, not quite the clever cross-examining lawyer advocate, not quite a philosopher-scientist, not a sceptic more than necessary, not quite embat tled in the bloody world but not ever above the battle either . . . but a good deal of all of these, and steeped in intelligence and good will.

Hybrid Censoring Know-How

Hybrid Censoring Know-How PDF Author: Narayanaswamy Balakrishnan
Publisher: Academic Press
ISBN: 0123983908
Category : Mathematics
Languages : en
Pages : 408
Book Description
Hybrid Censoring Know-How: Models, Methods and Applications focuses on hybrid censoring, an important topic in censoring methodology with numerous applications. The readers will find information on the significance of censored data in theoretical and applied contexts, and descriptions of extensive data sets from life-testing experiments where these forms of data naturally occur. The existing literature on censoring methodology, life-testing procedures, and lifetime data analysis provides only hybrid censoring schemes, with little information about hybrid censoring methodologies, ideas, and statistical inferential methods. This book fills that gap, featuring statistical tools applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography. Presents many numerical examples to adequately illustrate all inferential methods discussed Mentions some open problems and possible directions for future work Reviews developments on Type-II and Type-I HCS, including the most recent research and trends Explains why hybrid censored sampling is important in practice Provides details about the use of HCS under different settings and on various designs of HCS Describes the use of hybrid censoring in other reliability applications such as reliability sampling plans, step-stress testing, and quality control

Computational Statistics

Computational Statistics PDF Author: Geof H. Givens
Publisher: John Wiley & Sons
ISBN: 1118555481
Category : Mathematics
Languages : en
Pages : 496
Book Description
This new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing. The book is comprised of four main parts spanning the field: Optimization Integration and Simulation Bootstrapping Density Estimation and Smoothing Within these sections,each chapter includes a comprehensive introduction and step-by-step implementation summaries to accompany the explanations of key methods. The new edition includes updated coverage and existing topics as well as new topics such as adaptive MCMC and bootstrapping for correlated data. The book website now includes comprehensive R code for the entire book. There are extensive exercises, real examples, and helpful insights about how to use the methods in practice.

The Use Of Statistics In Forensic Science

The Use Of Statistics In Forensic Science PDF Author: C. G. G. Aitken
Publisher: CRC Press
ISBN: 0203017323
Category : Law
Languages : en
Pages : 242
Book Description
Describes ways of assessing forensic science evidence and the means of communicating the assessment to a court of law. The aim of this work is to ensure that the courts consider seriously the probability of the evidence of association.

Extreme Value Modeling and Risk Analysis

Extreme Value Modeling and Risk Analysis PDF Author: Dipak K. Dey
Publisher: CRC Press
ISBN: 1498701310
Category : Mathematics
Languages : en
Pages : 520
Book Description
Extreme Value Modeling and Risk Analysis: Methods and Applications presents a broad overview of statistical modeling of extreme events along with the most recent methodologies and various applications. The book brings together background material and advanced topics, eliminating the need to sort through the massive amount of literature on the subject. After reviewing univariate extreme value analysis and multivariate extremes, the book explains univariate extreme value mixture modeling, threshold selection in extreme value analysis, and threshold modeling of non-stationary extremes. It presents new results for block-maxima of vine copulas, develops time series of extremes with applications from climatology, describes max-autoregressive and moving maxima models for extremes, and discusses spatial extremes and max-stable processes. The book then covers simulation and conditional simulation of max-stable processes; inference methodologies, such as composite likelihood, Bayesian inference, and approximate Bayesian computation; and inferences about extreme quantiles and extreme dependence. It also explores novel applications of extreme value modeling, including financial investments, insurance and financial risk management, weather and climate disasters, clinical trials, and sports statistics. Risk analyses related to extreme events require the combined expertise of statisticians and domain experts in climatology, hydrology, finance, insurance, sports, and other fields. This book connects statistical/mathematical research with critical decision and risk assessment/management applications to stimulate more collaboration between these statisticians and specialists.

Generalized Latent Variable Modeling

Generalized Latent Variable Modeling PDF Author: Anders Skrondal
Publisher: CRC Press
ISBN: 0203489438
Category : Mathematics
Languages : en
Pages : 528
Book Description
This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and contrast a wi

Statistical Inference

Statistical Inference PDF Author: Ayanendranath Basu
Publisher: CRC Press
ISBN: 1420099663
Category : Computers
Languages : en
Pages : 429
Book Description
In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics. However, there are many different ways of constructing an appropriate distance between the data and the model: the scope of study referred to by "Minimum Distance Estimation" is literally huge. Filling a statistical resource gap, Statistical Inference: The Minimum Distance Approach comprehensively overviews developments in density-based minimum distance inference for independently and identically distributed data. Extensions to other more complex models are also discussed. Comprehensively covering the basics and applications of minimum distance inference, this book introduces and discusses: The estimation and hypothesis testing problems for both discrete and continuous models The robustness properties and the structural geometry of the minimum distance methods The inlier problem and its possible solutions, and the weighted likelihood estimation problem The extension of the minimum distance methodology in interdisciplinary areas, such as neural networks and fuzzy sets, as well as specialized models and problems, including semi-parametric problems, mixture models, grouped data problems, and survival analysis. Statistical Inference: The Minimum Distance Approach gives a thorough account of density-based minimum distance methods and their use in statistical inference. It covers statistical distances, density-based minimum distance methods, discrete and continuous models, asymptotic distributions, robustness, computational issues, residual adjustment functions, graphical descriptions of robustness, penalized and combined distances, weighted likelihood, and multinomial goodness-of-fit tests. This carefully crafted resource is useful to researchers and scientists within and outside the statistics arena.