Maximum Likelihood Estimation With Stata Third Edition
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Maximum Likelihood Estimation With Stata Third Edition
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Author : William Gould
language : en
Publisher: Stata Press
Release Date : 2006
Maximum Likelihood Estimation With Stata Third Edition written by William Gould and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Computers categories.
Written by the creators of Stata's likelihood maximization features, Maximum Likelihood Estimation with Stata, Third Edition continues the pioneering work of the previous editions. Emphasizing practical implications for applied work, the first chapter provides an overview of maximum likelihood estimation theory and numerical optimization methods. With step-by-step instructions, the next several chapters detail the use of Stata to maximize user-written likelihood functions. Various examples include logit, probit, linear, Weibull, and random-effects linear regression as well as the Cox proportional hazards model. The final chapters describe how to add a new estimation command to Stata. Assuming a familiarity with Stata, this reference is ideal for researchers who need to maximize their own likelihood functions. New ml commands and their functions: constraint: fits a model with linear constraints on the coefficient by defining your constraints; accepts a constraint matrix ml model: picks up survey characteristics; accepts the subpop option for analyzing survey data optimization algorithms: Berndt-Hall-Hall-Hausman (BHHH), Davidon-Fletcher-Powell (DFP), Broyden-Fletcher-Goldfarb-Shanno (BFGS) ml: switches between optimization algorithms; computes variance estimates using the outer product of gradients (OPG)
Maximum Likelihood Estimation With Stata
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Author : William Gould
language : en
Publisher:
Release Date : 2003
Maximum Likelihood Estimation With Stata written by William Gould and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Mathematics categories.
Maximum Likelihood Estimation With Stata
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Author : William Gould
language : en
Publisher:
Release Date : 2010
Maximum Likelihood Estimation With Stata written by William Gould and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Social sciences categories.
Maximum Likelihood Estimation with Stata, Fourth Edition is written for researchers in all disciplines who need to compute maximum likelihood estimators that are not available as prepackaged routines. Readers are presumed to be familiar with Stata, but no special programming skills are assumed except in the last few chapters, which detail how to add a new estimation command to Stata. The book begins with an introduction to the theory of maximum likelihood estimation with particular attention on the practical implications for applied work. Individual chapters then describe in detail each of the four types of likelihood evaluator programs and provide numerous examples, such as logit and probit regression, Weibull regression, random-effects linear regression, and the Cox proportional hazards model. Later chapters and appendixes provide additional details about the ml command, provide checklists to follow when writing evaluators, and show how to write your own estimation commands.
Maximum Likelihood Estimation With Stata Fourth Edition
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Author : William Gould
language : en
Publisher: Stata Press
Release Date : 2010-10-27
Maximum Likelihood Estimation With Stata Fourth Edition written by William Gould and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-27 with Mathematics categories.
Maximum Likelihood Estimation with Stata, Fourth Edition is written for researchers in all disciplines who need to compute maximum likelihood estimators that are not available as prepackaged routines. Readers are presumed to be familiar with Stata, but no special programming skills are assumed except in the last few chapters, which detail how to add a new estimation command to Stata. The book begins with an introduction to the theory of maximum likelihood estimation with particular attention on the practical implications for applied work. Individual chapters then describe in detail each of the four types of likelihood evaluator programs and provide numerous examples, such as logit and probit regression, Weibull regression, random-effects linear regression, and the Cox proportional hazards model. Later chapters and appendixes provide additional details about the ml command, provide checklists to follow when writing evaluators, and show how to write your own estimation commands.
Regression Models For Categorical Dependent Variables Using Stata
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Author : J. Scott Long
language : en
Publisher:
Release Date : 2006
Regression Models For Categorical Dependent Variables Using Stata written by J. Scott Long and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Regression analysis categories.
Handbook Of Statistical Analyses Using Stata
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Author : Sophia Rabe-Hesketh
language : en
Publisher: CRC Press
Release Date : 2003-12-23
Handbook Of Statistical Analyses Using Stata written by Sophia Rabe-Hesketh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-12-23 with Mathematics categories.
The powerful statistical software Stata has streamlined data analysis, interpretation, and presentation for researchers and statisticians around the world. But because of its power and plethora of features, particularly in version 8, Stata manuals are usually quite extensive and detailed. The third edition of the Handbook of Statistical Analyses Using Stata describes the features of Stata version 8 in the same concise, convenient format that made the previous editions so popular. But the revisions updating the handbook to version 8 are not all this edition has to offer: the authors also added important material in three all-new chapters and focused more attention on Stata's improved graphical features. More Highlights of the Third Edition Ö Updates in all chapters that reflect the features of Stata 8 Ö A new chapter on random effects models Ö A new chapter on generalized estimating equations Ö A new chapter on cluster analysis Ö Increased emphasis on diagnostics Each chapter deals with a particular data set, identifies the appropriate analysis for it, and while it includes a brief account of the statistical background of the technique applied, the primary focus remains firmly on using Stata 8 and interpreting its results. Ideal for researchers, statisticians, and students alike, this handbook forms a perfect complement to the Stata manuals, by giving new users a head start on using the program and providing experienced users with a handy quick reference.
Regression Models For Categorical Dependent Variables Using Stata Second Edition
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Author : J. Scott Long
language : en
Publisher: Stata Press
Release Date : 2006
Regression Models For Categorical Dependent Variables Using Stata Second Edition written by J. Scott Long and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Computers categories.
The goal of the book is to make easier to carry out the computations necessary for the full interpretation of regression nonlinear models for categorical outcomes usign Stata.
Handbook Of Statistical Analyses Using Stata
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Author : Brian S. Everitt
language : en
Publisher: CRC Press
Release Date : 2006-11-15
Handbook Of Statistical Analyses Using Stata written by Brian S. Everitt and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-11-15 with Mathematics categories.
With each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. Fulfilling this need, AHandbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9. This edition covers many
Data Analysis Using Stata
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Author : Ulrich Kohler (Dr. phil.)
language : en
Publisher: Stata Press
Release Date : 2005-06-15
Data Analysis Using Stata written by Ulrich Kohler (Dr. phil.) and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-06-15 with Computers categories.
"This book provides a comprehensive introduction to Stata with an emphasis on data management, linear regression, logistic modeling, and using programs to automate repetitive tasks. Using data from a longitudinal study of private households in Germany, the book presents many examples from the social sciences to bring beginners up to speed on the use of Stata." -- BACK COVER.
An Introduction To Generalized Linear Models
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Author : Annette J. Dobson
language : en
Publisher: CRC Press
Release Date : 2008-05-12
An Introduction To Generalized Linear Models written by Annette J. Dobson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-12 with Mathematics categories.
Continuing to emphasize numerical and graphical methods, An Introduction to Generalized Linear Models, Third Edition provides a cohesive framework for statistical modeling. This new edition of a bestseller has been updated with Stata, R, and WinBUGS code as well as three new chapters on Bayesian analysis. Like its predecessor, this edition presents the theoretical background of generalized linear models (GLMs) before focusing on methods for analyzing particular kinds of data. It covers normal, Poisson, and binomial distributions; linear regression models; classical estimation and model fitting methods; and frequentist methods of statistical inference. After forming this foundation, the authors explore multiple linear regression, analysis of variance (ANOVA), logistic regression, log-linear models, survival analysis, multilevel modeling, Bayesian models, and Markov chain Monte Carlo (MCMC) methods. Using popular statistical software programs, this concise and accessible text illustrates practical approaches to estimation, model fitting, and model comparisons. It includes examples and exercises with complete data sets for nearly all the models covered.