Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Statistical Models
Download Statistical Models full books in PDF, epub, and Kindle. Read online Statistical Models ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Statistical Models by : David A. Freedman
Download or read book Statistical Models written by David A. Freedman and published by Cambridge University Press. This book was released on 2009-04-27 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedman makes a thorough appraisal of the statistical methods in these papers and in a variety of other examples. He illustrates the principles of modelling, and the pitfalls. The discussion shows you how to think about the critical issues - including the connection (or lack of it) between the statistical models and the real phenomena. The book is written for advanced undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.
Book Synopsis Linear Statistical Models by : James H. Stapleton
Download or read book Linear Statistical Models written by James H. Stapleton and published by John Wiley & Sons. This book was released on 2009-08-03 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "This impressive and eminently readable text . . . [is] a welcome addition to the statistical literature." —The Indian Journal of Statistics Revised to reflect the current developments on the topic, Linear Statistical Models, Second Edition provides an up-to-date approach to various statistical model concepts. The book includes clear discussions that illustrate key concepts in an accessible and interesting format while incorporating the most modern software applications. This Second Edition follows an introduction-theorem-proof-examples format that allows for easier comprehension of how to use the methods and recognize the associated assumptions and limits. In addition to discussions on the methods of random vectors, multiple regression techniques, simultaneous confidence intervals, and analysis of frequency data, new topics such as mixed models and curve fitting of models have been added to thoroughly update and modernize the book. Additional topical coverage includes: An introduction to R and S-Plus® with many examples Multiple comparison procedures Estimation of quantiles for regression models An emphasis on vector spaces and the corresponding geometry Extensive graphical displays accompany the book's updated descriptions and examples, which can be simulated using R, S-Plus®, and SAS® code. Problems at the end of each chapter allow readers to test their understanding of the presented concepts, and additional data sets are available via the book's FTP site. Linear Statistical Models, Second Edition is an excellent book for courses on linear models at the upper-undergraduate and graduate levels. It also serves as a comprehensive reference for statisticians, engineers, and scientists who apply multiple regression or analysis of variance in their everyday work.
Book Synopsis Statistical Models by : A. C. Davison
Download or read book Statistical Models written by A. C. Davison and published by Cambridge University Press. This book was released on 2008-06-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Models and likelihood are the backbone of modern statistics and data analysis. The coverage is unrivaled, with sections on survival analysis, missing data, Markov chains, Markov random fields, point processes, graphical models, simulation and Markov chain Monte Carlo, estimating functions, asymptotic approximations, local likelihood and spline regressions as well as on more standard topics. Anthony Davison blends theory and practice to provide an integrated text for advanced undergraduate and graduate students, researchers and practicioners. Its comprehensive coverage makes this the standard text and reference in the subject.
Book Synopsis Statistical Models in S by : T.J. Hastie
Download or read book Statistical Models in S written by T.J. Hastie and published by Routledge. This book was released on 2017-11-01 with total page 673 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Models in S extends the S language to fit and analyze a variety of statistical models, including analysis of variance, generalized linear models, additive models, local regression, and tree-based models. The contributions of the ten authors-most of whom work in the statistics research department at AT&T Bell Laboratories-represent results of research in both the computational and statistical aspects of modeling data.
Book Synopsis Statistical Models Based on Counting Processes by : Per K. Andersen
Download or read book Statistical Models Based on Counting Processes written by Per K. Andersen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 779 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern survival analysis and more general event history analysis may be effectively handled within the mathematical framework of counting processes. This book presents this theory, which has been the subject of intense research activity over the past 15 years. The exposition of the theory is integrated with careful presentation of many practical examples, drawn almost exclusively from the authors'own experience, with detailed numerical and graphical illustrations. Although Statistical Models Based on Counting Processes may be viewed as a research monograph for mathematical statisticians and biostatisticians, almost all the methods are given in concrete detail for use in practice by other mathematically oriented researchers studying event histories (demographers, econometricians, epidemiologists, actuarial mathematicians, reliability engineers and biologists). Much of the material has so far only been available in the journal literature (if at all), and so a wide variety of researchers will find this an invaluable survey of the subject.
Book Synopsis Statistical Models and Methods for Financial Markets by : Tze Leung Lai
Download or read book Statistical Models and Methods for Financial Markets written by Tze Leung Lai and published by Springer Science & Business Media. This book was released on 2008-09-08 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: The idea of writing this bookarosein 2000when the ?rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in ?nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master’s-level education in applied mathematics, statistics, computing, ?nance, and economics. Students in the programhad di?erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in ?nance. To address the diversity in background but common strong interest in the subject and in a potential career as a “quant” in the ?nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative ?nance but also to summarize domain knowledge in ?nance and show how it can be combined with statistical modeling in ?nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005.
Book Synopsis Statistical Models and Methods for Lifetime Data by : Jerald F. Lawless
Download or read book Statistical Models and Methods for Lifetime Data written by Jerald F. Lawless and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "An indispensable addition to any serious collection on lifetime data analysis and . . . a valuable contribution to the statistical literature. Highly recommended . . ." -Choice "This is an important book, which will appeal to statisticians working on survival analysis problems." -Biometrics "A thorough, unified treatment of statistical models and methods used in the analysis of lifetime data . . . this is a highly competent and agreeable statistical textbook." -Statistics in Medicine The statistical analysis of lifetime or response time data is a key tool in engineering, medicine, and many other scientific and technological areas. This book provides a unified treatment of the models and statistical methods used to analyze lifetime data. Equally useful as a reference for individuals interested in the analysis of lifetime data and as a text for advanced students, Statistical Models and Methods for Lifetime Data, Second Edition provides broad coverage of the area without concentrating on any single field of application. Extensive illustrations and examples drawn from engineering and the biomedical sciences provide readers with a clear understanding of key concepts. New and expanded coverage in this edition includes: * Observation schemes for lifetime data * Multiple failure modes * Counting process-martingale tools * Both special lifetime data and general optimization software * Mixture models * Treatment of interval-censored and truncated data * Multivariate lifetimes and event history models * Resampling and simulation methodology
Book Synopsis Statistical Modeling and Computation by : Dirk P. Kroese
Download or read book Statistical Modeling and Computation written by Dirk P. Kroese and published by Springer Science & Business Media. This book was released on 2013-11-18 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook on statistical modeling and statistical inference will assist advanced undergraduate and graduate students. Statistical Modeling and Computation provides a unique introduction to modern Statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of Mathematical Statistics and modern statistical computation, emphasizing statistical modeling, computational techniques, and applications. Each of the three parts will cover topics essential to university courses. Part I covers the fundamentals of probability theory. In Part II, the authors introduce a wide variety of classical models that include, among others, linear regression and ANOVA models. In Part III, the authors address the statistical analysis and computation of various advanced models, such as generalized linear, state-space and Gaussian models. Particular attention is paid to fast Monte Carlo techniques for Bayesian inference on these models. Throughout the book the authors include a large number of illustrative examples and solved problems. The book also features a section with solutions, an appendix that serves as a MATLAB primer, and a mathematical supplement.
Book Synopsis Applied Linear Statistical Models by : Michael H. Kutner
Download or read book Applied Linear Statistical Models written by Michael H. Kutner and published by McGraw-Hill Education. This book was released on 2005 with total page 1396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Linear Statistical Models 5e is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.
Book Synopsis Nonlinear Statistical Models by : A. Ronald Gallant
Download or read book Nonlinear Statistical Models written by A. Ronald Gallant and published by John Wiley & Sons. This book was released on 1987-02-04 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: Univariate nonlinear regression; Univariate nonlinear regression: special situations; A unified asymptotic theory of nonlinear models with regression structure; Univariate nonlinear regression: asymptotic theory; Multivariate nonlinear regression; Nonlinear simultaneus equations models; A unified asymptotic theory for dynamic nonlinear models.
Book Synopsis Statistical Models and Causal Inference by : David A. Freedman
Download or read book Statistical Models and Causal Inference written by David A. Freedman and published by Cambridge University Press. This book was released on 2010 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: David A. Freedman presents a definitive synthesis of his approach to statistical modeling and causal inference in the social sciences.
Book Synopsis Linear Statistical Models by : Bruce L. Bowerman
Download or read book Linear Statistical Models written by Bruce L. Bowerman and published by Brooks/Cole. This book was released on 2000-03-24 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The focus of Linear Statistical Models: An Applied Approach, Second Editon, is on the conceptual, concrete, and applied aspects of model building, data analysis, and interpretaion. Without sacrificing depth and breadth of coverage, Bruce L. Bowerman and Richard T. O'Connell's clear and concise explanantions make the material accessible even to those with limited statistical experience.
Book Synopsis Statistical Models in Behavioral Research by : William Kaye Estes
Download or read book Statistical Models in Behavioral Research written by William Kaye Estes and published by Psychology Press. This book was released on 1991 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: First Published in 1991. Routledge is an imprint of Taylor & Francis, an informa company.
Book Synopsis Mathematical and Statistical Models and Methods in Reliability by : V.V. Rykov
Download or read book Mathematical and Statistical Models and Methods in Reliability written by V.V. Rykov and published by Springer Science & Business Media. This book was released on 2010-11-02 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a selection of invited chapters, all of which deal with various aspects of mathematical and statistical models and methods in reliability. Written by renowned experts in the field of reliability, the contributions cover a wide range of applications, reflecting recent developments in areas such as survival analysis, aging, lifetime data analysis, artificial intelligence, medicine, carcinogenesis studies, nuclear power, financial modeling, aircraft engineering, quality control, and transportation. Mathematical and Statistical Models and Methods in Reliability is an excellent reference text for researchers and practitioners in applied probability and statistics, industrial statistics, engineering, medicine, finance, transportation, the oil and gas industry, and artificial intelligence.
Book Synopsis Statistical Models of Shape by : Rhodri Davies
Download or read book Statistical Models of Shape written by Rhodri Davies and published by Springer Science & Business Media. This book was released on 2008-12-15 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of image interpretation is to convert raw image data into me- ingful information. Images are often interpreted manually. In medicine, for example, a radiologist looks at a medical image, interprets it, and tra- lates the data into a clinically useful form. Manual image interpretation is, however, a time-consuming, error-prone, and subjective process that often requires specialist knowledge. Automated methods that promise fast and - jective image interpretation have therefore stirred up much interest and have become a signi?cant area of research activity. Early work on automated interpretation used low-level operations such as edge detection and region growing to label objects in images. These can p- ducereasonableresultsonsimpleimages,butthepresenceofnoise,occlusion, andstructuralcomplexity oftenleadstoerroneouslabelling. Furthermore,- belling an object is often only the ?rst step of the interpretation process. In order to perform higher-level analysis, a priori information must be incor- rated into the interpretation process. A convenient way of achieving this is to use a ?exible model to encode information such as the expected size, shape, appearance, and position of objects in an image. The use of ?exible models was popularized by the active contour model, or ‘snake’ [98]. A snake deforms so as to match image evidence (e.g., edges) whilst ensuring that it satis?es structural constraints. However, a snake lacks speci?city as it has little knowledge of the domain, limiting its value in image interpretation.
Book Synopsis Statistical Models in Epidemiology by : David Clayton
Download or read book Statistical Models in Epidemiology written by David Clayton and published by Oxford University Press, USA. This book was released on 2013-01-17 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This self-contained account of the statistical basis of epidemiology has been written for those with a basic training in biology. It is specifically intended for students enrolled for a masters degree in epidemiology, clinical epidemiology, or biostatistics.
Book Synopsis Applied Linear Regression Models by : Michael H. Kutner
Download or read book Applied Linear Regression Models written by Michael H. Kutner and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
