Extending the linear model with R: generalized linear, mixed effects and non parametric regression models (Record no. 205352)

000 -LEADER
fixed length control field 04799cam a2200229 i 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 151207t20162016flua b 001 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781498720960
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.538
Item number F2E9-2016
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Faraway, Julian James
9 (RLIN) 338857
245 10 - TITLE STATEMENT
Title Extending the linear model with R: generalized linear, mixed effects and non parametric regression models
250 ## - EDITION STATEMENT
Edition statement 2nd ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc New York
Name of publisher, distributor, etc CRC Press, Taylor and Francis
Date of publication, distribution, etc 2016
300 ## - PHYSICAL DESCRIPTION
Extent xiii, 399 p.
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Chapman and hall/CRC texts in statistical science series
9 (RLIN) 56351
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Table of Contents


1. INTRODUCTION

2. BINOMIAL DATA
Challenger Disaster Example
Binomial Regression Model
Inference
Tolerance Distribution
Interpreting Odds
Prospective and Retrospective Sampling
Choice of Link Function
Estimation Problems
Goodness of Fit
Prediction and Effective Doses
Overdispersion
Matched Case-Control Studies
3.

COUNT REGRESSION
Poisson Regression
Rate Models
Negative Binomial
4.

CONTINGENCY TABLES
Two-by-Two Tables
Larger Two-Way Tables
Matched Pairs
Three-Way Contingency Tables
Ordinal Variables
5.

MULTINOMIAL DATA
Multinomial Logit Model
Hierarchical or Nested Responses
Ordinal Multinomial Responses
6.

GENERALIZED LINEAR MODELS
GLM Definition
Fitting a GLM
Hypothesis Tests
GLM Diagnostics

7. OTHER GLMS
Gamma GLM
Inverse Gaussian GLM
Joint Modeling of the Mean and Dispersion
Quasi-Likelihood

8.
RANDOM EFFECTS
Estimation
Inference
Predicting Random Effects
Blocks as Random Effects
Split Plots
Nested Effects
Crossed Effects
Multilevel Models

9. REPEATED MEASURES AND LONGITUDINAL DATA
Longitudinal Data
Repeated Measures
Multiple Response Multilevel Models

10.
MIXED EFFECT MODELS FOR NONNORMAL RESPONSES
Generalized Linear Mixed Models
Generalized Estimating Equations

11. NONPARAMETRIC REGRESSION
Kernel Estimators
Splines
Local Polynomials
Wavelets
Other Methods
Comparison of Methods
Multivariate Predictors

12. ADDITIVE MODELS
Additive Models Using the gam Package
Additive Models Using mgcv
Generalized Additive Models
Alternating Conditional Expectations
Additivity and Variance Stabilization
Generalized Additive Mixed Models
Multivariate Adaptive Regression Splines

13. TREES
Regression Trees
Tree Pruning
Classification Trees

14. NEURAL NETWORKS
Statistical Models as NNs
Feed-Forward Neural Network with One Hidden Layer
NN Application
Conclusion
15.

APPENDICES
Likelihood Theory
R Information
Bibliography
Index


520 ## - SUMMARY, ETC.
Summary, etc Features

Offers an outstanding practical survey of statistical methods extended from the regression model
Presents all of the linear model extensions using a common framework, making estimation, inference, and model building and checking clearly understandable
Includes an introductory chapter that reviews the linear model and the basics of using R
Provides a companion website featuring all of the datasets used in the book
Summary

Linear models are central to the practice of statistics and form the foundation of a vast range of statistical methodologies. Julian J. Faraway's critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods available, and showed in which situations each one applies.

Following in those footsteps, Extending the Linear Model with R surveys the techniques that grow from the regression model, presenting three extensions to that framework: generalized linear models (GLMs), mixed effect models, and nonparametric regression models. The author's treatment is thoroughly modern and covers topics that include GLM diagnostics, generalized linear mixed models, trees, and even the use of neural networks in statistics. To demonstrate the interplay of theory and practice, throughout the book the author weaves the use of the R software environment to analyze the data of real examples, providing all of the R commands necessary to reproduce the analyses. All of the data described in the book is available at http://people.bath.ac.uk/jjf23/ELM/

Statisticians need to be familiar with a broad range of ideas and techniques. This book provides a well-stocked toolbox of methodologies, and with its unique presentation of these very modern statistical techniques, holds the potential to break new ground in the way graduate-level courses in this area are taught.


https://www.crcpress.com/Extending-the-Linear-Model-with-R-Generalized-Linear-Mixed-Effects-and/Faraway/p/book/9781584884248
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Analysis of variance
9 (RLIN) 36669
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Regression analysis
9 (RLIN) 27678
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer program language
9 (RLIN) 338858
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematical models
9 (RLIN) 638
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Permanent location Current location Shelving location Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Total Renewals Full call number Barcode Date last seen Date last borrowed Cost, replacement price Koha item type
          Non-fiction Vikram Sarabhai Library Vikram Sarabhai Library General Stacks 2017-01-10 6 4510.01 3 5 519.538 F2E9-2016 193519 2019-03-18 2018-09-16 5637.52 Books

Powered by Koha