Fitting paired comparison models in R
Paired comparison models in loglinear form are generalised linear models and can be fitted using the IWLS algorithm. Unfortunately, the design matrices can become very large and thus a method is needed to reduce computational load (relating to both space and time). This paper discusses an algorithm...
| Main Authors: | , |
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| Format: | Others |
| Language: | en |
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Institut für Statistik und Mathematik, WU Vienna University of Economics and Business
2004
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| Subjects: | |
| Online Access: | http://epub.wu.ac.at/740/1/document.pdf |
| Summary: | Paired comparison models in loglinear form are generalised linear models and can be fitted using the IWLS algorithm. Unfortunately, the design matrices can become very large and thus a method is needed to reduce computational load (relating to both space and time). This paper discusses an algorithm for fitting loglinear paired comparison models in the presence of many nuisance parameters which is based on partition rules for symmetric matrices and takes advantage of the special structure of the design matrix in Poisson loglinear models. The algorithm is implemented as an R function. Some simple examples illustrate its use for fitting both paired comparison models and (multinomial) logit models. (author's abstract) === Series: Research Report Series / Department of Statistics and Mathematics |
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