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GLIM 82: Proceedings of the International Conference on Generalised Linear Models
Tag	Description
020	$a9781461257714$9978-1-4612-5771-4
082	$a519$223
099	$aOnline resource: Springer
245	$aGLIM 82: Proceedings of the International Conference on Generalised Linear Models$h[EBook] /$cedited by Robert Gilchrist.
260	$aNew York, NY :$bSpringer New York,$c1982.
300	$a188 p.$bonline resource.
336	$atext$btxt$2rdacontent
337	$acomputer$bc$2rdamedia
338	$aonline resource$bcr$2rdacarrier
440	$aLecture Notes in Statistics,$x0930-0325 ;$v14
505	$aPrism, an Overview -- GLIM4 — The New Facilities -- Array Manipulation in Prism -- The Graph Module -- AOV: The Prism Module for Analysing Designed Experiments -- The Apl Alternative -- Direct Likelihood Inference -- Score Tests in Glim -- GLIM Syntax and Simultaneous Tests for Graphical Log Linear Models -- Compound Poisson Regression Models -- Some Aspects of Parametric Link Functions -- A Model for a Binary Response with Misclassifications -- Loglinear Models with Composite Link Functions in Genetics -- Use of the Complementary Log-Log Function to Describe Dose-Response Relationships in Insecticide Evalation Field Trials -- Glim for Preference -- A Glm for Estimating Probabilities in Retrospective Case-Control Studies.
520	$aThis volume of Lecture Notes in Statistics consists of the published proceedings of the first international conference to be held on the topic of generalised linear models. This conference was held from 13 - 15 September 1982 at the Polytechnic of North London and marked an important stage in the development and expansion of the GLIM system. The range of the new system, tentatively named Prism, is here outlined by Bob Baker. Further sections of the volume are devoted to more detailed descriptions of the new facilities, including information on the two different numerical methods now available. Most of the data analyses in this volume are carried out using the GLIM system but this is, of course, not necessary. There are other ways of analysing generalised linear models and Peter Green here discusses the many attractive features of APL, including its ability to analyse generalised linear models. Later sections of the volume cover other invited and contributed papers on the theory and application of generalised linear models. Included amongst these is a paper by Murray Aitkin, proposing a unified approach to statistical modelling through direct likelihood inference, and a paper by Daryl Pregibon showing how GLIM can be programmed to carry out score tests. A paper by Joe Whittaker extends the recent discussion of the relationship between conditional independence and log-linear models and John Hinde considers the introduction of an independent random variable into a linear model to allow for unexplained variation in Poisson data.
538	$aOnline access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
700	$aGilchrist, Robert.$eeditor.
710	$aSpringerLink (Online service)
830	$aLecture Notes in Statistics,$x0930-0325 ;$v14
856	$uhttp://dx.doi.org/10.1007/978-1-4612-5771-4