By J. A. Nelder (auth.), Robert Gilchrist (eds.)
This quantity of Lecture Notes in statistics contains the broadcast court cases of the 1st foreign convention to be hung on the subject of generalised linear types. This convention was once held from thirteen - 15 September 1982 on the Polytechnic of North London and marked an immense degree within the improvement and growth of the GLIM procedure. the variety of the hot method, tentatively named Prism, is the following defined by way of Bob Baker. extra sections of the quantity are dedicated to extra targeted descriptions of the hot amenities, together with info at the assorted numerical tools now to be had. many of the facts analyses during this quantity are conducted utilizing the GLIM process yet this can be, in fact, no longer valuable. There are alternative routes of analysing generalised linear types and Peter eco-friendly right here discusses the numerous appealing beneficial properties of APL, together with its skill to examine generalised linear versions. Later sections of the amount hide different invited and contributed papers at the thought and alertness of generalised linear types. integrated among those is a paper through Murray Aitkin, presenting a unified method of statistical modelling via direct chance inference, and a paper by way of Daryl Pregibon displaying how GLIM could be programmed to hold out rating assessments. A paper via Joe Whittaker extends the hot dialogue of the connection among conditional independence and log-linear types and John Hinde considers the advent of an self sufficient random variable right into a linear version to permit for unexplained edition in Poisson data.
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Additional resources for GLIM 82: Proceedings of the International Conference on Generalised Linear Models
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O! ~ (f). LJ! : ~........... ~:: I ~ < 0' CD Cl. :J. ~ ~ L:::::: I L...... : • /' I ............ ::1 .... ~ all Fig. LL·- L Q) +--' +--' CJ) . n ( 0 - 0... (f) 0 U 0 Z 55 ... ~ ... Q. 0 ~ 0 0 0 .... "i:0 ::l Q. - \ 56 . PAYNE Statistics Department, Rothamsted Experimental Station, Harpenden, Herts SUMMARY A brief description is given of the scope and syntax of AOV, together with an ex~~ple illustrating the sort of output that can be obtained. Keywords: ANALYSIS OF VARIANCE; COMPUTER PROGRAMS; STATISTICAL COMPUTING; STATISTICAL PACKAGES 1.
F) 0 U 0 Z 55 ... ~ ... Q. 0 ~ 0 0 0 .... "i:0 ::l Q. - \ 56 . PAYNE Statistics Department, Rothamsted Experimental Station, Harpenden, Herts SUMMARY A brief description is given of the scope and syntax of AOV, together with an ex~~ple illustrating the sort of output that can be obtained. Keywords: ANALYSIS OF VARIANCE; COMPUTER PROGRAMS; STATISTICAL COMPUTING; STATISTICAL PACKAGES 1. INTRODUC TI ON The AOV module of Prism was initially conceived as a sister program to GLIM, which would be formed by linking the GLIM housekeeping routines to the analysis of variance algorithm from Genstat Mk.
At the time of writing we are also conSidering the provision of a mechanism enabling the user to specify a superset of variates the intersection of whose complete data sets defines the set of units to be used in subsequent fits. 33 7. NUMERICAL METHOD It would be possible to write a substantial paper on this topic alone and the view that the details should remain hidden from the user is an entirely reasonable one. Nevertheless the basic ideas can be quite easily explained. Consider a single iteration and ignore for simplicity the iterative weight.