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Methods of Statistical Model Estimation

By Joseph Hilbe

Methods of Statistical Model Estimation Mathematics

Methods of Statistical Model Estimation

By Joseph Hilbe

0 - Default Title
Description
This book examines the most important and popular methods used to estimate parameters for statistical models and provide informative model summary statistics. Designed for R users, the book is also ideal for anyone wanting to better understand the algorithms used for statistical model fitting. It presents algorithms for the estimation of a variety of useful regression procedures using maximum likelihood estimation, iteratively reweighted least squares regression, the EM algorithm, and MCMC sampling. Fully developed, working R code is constructed for each method.
Product details
Binding:
Paperback
Edition:
1
Number of Pages:
256
Release Date:
2019-09-05
Publication Date:
2019-09-05
Publisher:
Chapman and Hall/CRC
Languages:
Original: English
ISBN10:
0367380005
ISBN13:
9780367380007
GPSR Manufacturer Reference:
[email protected]
Weight:
395 g
Height:
156 cm
Width:
234 cm
Thickness:
14 cm
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