logo
Product categories

EbookNice.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link.  https://ebooknice.com/page/post?id=faq


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookNice Team

(Ebook) An Introduction to Generalized Linear Models, Third Edition by Barnett, Adrian; Dobson, Annette J ISBN 9781584889519, 1584889519

  • SKU: EBN-5143964
Zoomable Image
$ 32 $ 40 (-20%)

Status:

Available

5.0

31 reviews
Instant download (eBook) An Introduction to Generalized Linear Models, Third Edition after payment.
Authors:Barnett, Adrian; Dobson, Annette J
Pages:316 pages.
Year:2008
Editon:3rd ed
Publisher:CRC Press
Language:english
File Size:3.38 MB
Format:pdf
ISBNS:9781584889519, 1584889519
Categories: Ebooks

Product desciption

(Ebook) An Introduction to Generalized Linear Models, Third Edition by Barnett, Adrian; Dobson, Annette J ISBN 9781584889519, 1584889519

Introduction Background Scope Notation Distributions Related to the Normal Distribution Quadratic Forms Estimation Model Fitting Introduction Examples Some Principles of Statistical Modeling Notation and Coding for Explanatory Variables Exponential Family and Generalized Linear Models Introduction Exponential Family of Distributions Properties of Distributions in the Exponential Family Generalized Linear Models Examples Estimation Introduction Example: Failure Times for Pressure Vessels Maximum Likelihood Estimation Poisson Regression Example Inference Introduct.
Abstract: Offers a cohesive framework for statistical modeling. Emphasizing numerical and graphical methods, this work enables readers to understand the unifying structure that underpins GLMs. It discusses common concepts and principles of advanced GLMs, including nominal and ordinal regression, survival analysis, and longitudinal analysis.
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

Related Products