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.
General
| Imprint: |
Taylor & Francis
|
| Country of origin: |
United Kingdom |
| Series: |
Chapman & Hall/CRC Interdisciplinary Statistics |
| Release date: |
June 2021 |
| First published: |
2019 |
| Authors: |
Kenneth G. Russell
|
| Dimensions: |
229 x 152mm (L x W) |
| Format: |
Paperback
|
| Pages: |
240 |
| ISBN-13: |
978-1-03-209405-2 |
| Categories: |
Books >
Science & Mathematics >
Mathematics >
Probability & statistics
|
| LSN: |
1-03-209405-2 |
| Barcode: |
9781032094052 |
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