Nonparametric Regression and Generalized Linear Models : A roughness penalty approach
Book Details
Format
Hardback or Cased Book
ISBN-10
0412300400
ISBN-13
9780412300400
Publisher
Taylor & Francis Ltd
Imprint
Chapman & Hall/CRC
Country of Manufacture
GB
Country of Publication
GB
Publication Date
May 1st, 1993
Print length
194 Pages
Weight
414 grams
Dimensions
16.20 x 23.20 x 1.60 cms
Product Classification:
AlgebraProbability & statisticsMathematical modelling
Ksh 34,200.00
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This study of nonparametric regression and generalized linear models contains chapters on approaches to regression, roughness penalties, extensions of the roughness penalty approach, computing the estimates, interpolating and smoothing splines, one-dimensional case, partial splines, and more.
In recent years, there has been a great deal of interest and activity in the general area of nonparametric smoothing in statistics. This monograph concentrates on the roughness penalty method and shows how this technique provides a unifying approach to a wide range of smoothing problems. The method allows parametric assumptions to be realized in regression problems, in those approached by generalized linear modelling, and in many other contexts.
The emphasis throughout is methodological rather than theoretical, and it concentrates on statistical and computation issues. Real data examples are used to illustrate the various methods and to compare them with standard parametric approaches. Some publicly available software is also discussed. The mathematical treatment is self-contained and depends mainly on simple linear algebra and calculus.
This monograph will be useful both as a reference work for research and applied statisticians and as a text for graduate students and other encountering the material for the first time.
The emphasis throughout is methodological rather than theoretical, and it concentrates on statistical and computation issues. Real data examples are used to illustrate the various methods and to compare them with standard parametric approaches. Some publicly available software is also discussed. The mathematical treatment is self-contained and depends mainly on simple linear algebra and calculus.
This monograph will be useful both as a reference work for research and applied statisticians and as a text for graduate students and other encountering the material for the first time.
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