Statistical Theory & Methods

PUBLISHED


Viewing: 1 - 10 of 378
Published:
July 22, 2014
Author(s):
John Chen
Multivariate Bonferroni-Type Inequalities: Theory and Applications presents a systematic account of research discoveries on multivariate Bonferroni-type inequalities published in the past decade. The emergence of new bounding approaches pushes the conventional definitions of optimal inequalities 
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Published:
July 17, 2014
Author(s):
Brady T. West, Kathleen B. Welch, Andrzej T Galecki
Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues 
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Published:
July 17, 2014
Author(s):
Ken Kleinman, Nicholas J. Horton
An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent TasksThe first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. Retaining the same accessible format, SAS and R: Data Management, Statistical Analysis, 
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Published:
July 07, 2014
Author(s):
Patrick Laurie Davies
The First Detailed Account of Statistical Analysis That Treats Models as Approximations The idea of truth plays a role in both Bayesian and frequentist statistics. The Bayesian concept of coherence is based on the fact that two different models or parameter values cannot both be true. Frequentist 
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Published:
July 01, 2014
Author(s):
Julian J. Faraway
A Hands-On Way to Learning Data Analysis Part of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with 
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Published:
June 26, 2014
Author(s):
Harry Joe
Dependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including vine copula modeling of high-dimensional data. Vine copula models are constructed from a sequence of bivariate copulas. The book develops generalizations of vine 
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Published:
June 26, 2014
Author(s):
John Verzani
The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the 
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Published:
June 25, 2014
Author(s):
Torsten Hothorn, Brian S. Everitt
Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive 
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Paperback
Published:
June 23, 2014
Author(s):
Arijit Chaudhuri
Starting from the preliminaries through live examples, the author tells the story about what a sample intends to communicate to a reader about the unknowable aggregate in a real situation. The story develops its own logic and a motivation for the reader to put up with, herein follows. Various 
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Published:
June 13, 2014
Author(s):
W. Holmes Finch, Jocelyn E. Bolin, Ken Kelley
A powerful tool for analyzing nested designs in a variety of fields, multilevel/hierarchical modeling allows researchers to account for data collected at multiple levels. Multilevel Modeling Using R provides you with a helpful guide to conducting multilevel data modeling using the R software 
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