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Design of Experiments for Generalized Linear Models

Af: Kenneth G. Russell Engelsk Paperback
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Design of Experiments for Generalized Linear Models

Af: Kenneth G. Russell Engelsk Paperback

Generalized Linear Models (GLMs) allow many statistical analyses to be extended to important statistical distributions other than the Normal distribution. While numerous books exist on how to analyse data using a GLM, little information is available on how to collect the data that are to be analysed in this way.



This is the first book focusing specifically on the design of experiments for GLMs. Much of the research literature on this topic is at a high mathematical level, and without any information on computation. This book explains the motivation behind various techniques, reduces the difficulty of the mathematics, or moves it to one side if it cannot be avoided, and gives examples of how to write and run computer programs using R.



Features





  • The generalisation of the linear model to GLMs


  • Background mathematics, and the use of constrained optimisation in R


  • Coverage of the theory behind the optimality of a design


  • Individual chapters on designs for data that have Binomial or Poisson distributions


  • Bayesian experimental design


  • An online resource contains R programs used in the book


This book is aimed at readers who have done elementary differentiation and understand minimal matrix algebra, and have familiarity with R. It equips professional statisticians to read the research literature. Nonstatisticians will be able to design their own experiments by following the examples and using the programs provided.



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Generalized Linear Models (GLMs) allow many statistical analyses to be extended to important statistical distributions other than the Normal distribution. While numerous books exist on how to analyse data using a GLM, little information is available on how to collect the data that are to be analysed in this way.



This is the first book focusing specifically on the design of experiments for GLMs. Much of the research literature on this topic is at a high mathematical level, and without any information on computation. This book explains the motivation behind various techniques, reduces the difficulty of the mathematics, or moves it to one side if it cannot be avoided, and gives examples of how to write and run computer programs using R.



Features





  • The generalisation of the linear model to GLMs


  • Background mathematics, and the use of constrained optimisation in R


  • Coverage of the theory behind the optimality of a design


  • Individual chapters on designs for data that have Binomial or Poisson distributions


  • Bayesian experimental design


  • An online resource contains R programs used in the book


This book is aimed at readers who have done elementary differentiation and understand minimal matrix algebra, and have familiarity with R. It equips professional statisticians to read the research literature. Nonstatisticians will be able to design their own experiments by following the examples and using the programs provided.



Produktdetaljer
Sprog: Engelsk
Sider: 240
ISBN-13: 9781032094052
Indbinding: Paperback
Udgave:
ISBN-10: 1032094052
Udg. Dato: 30 jun 2021
Længde: 0mm
Bredde: 229mm
Højde: 152mm
Forlag: Taylor & Francis Ltd
Oplagsdato: 30 jun 2021
Forfatter(e): Kenneth G. Russell
Forfatter(e) Kenneth G. Russell


Kategori Sandsynlighedsregning og statistik


Sprog Engelsk


Indbinding Paperback


Sider 240


Udgave


Længde 0mm


Bredde 229mm


Højde 152mm


Udg. Dato 30 jun 2021


Oplagsdato 30 jun 2021

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