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PAPERS PRESENTED IN THE GLIM WORKING PARTY SESSION
Structure and development
The Glimpse System
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algorithm alleles application approach approximation assumed assumption asymptotic binary binomial bootstrap break point CGLM coefficients column component computing conditional confidence intervals consider contingency tables convergence covariance matrix defined denote derived discussed distribution equation example explanatory variables exponential family extended facilities factor finite Genstat given GLIM graph graphical independent interaction interpretation iterative Kalman filter Keywords latent budgets least squares lemma likelihood function linear models linear predictor link function log-likelihood log-linear models log-log logistic regression logit model macro MANOVA maximum likelihood estimates McCullagh mean menarche method multinomial Nelder normal NSLA observations obtained ordinal overdispersion package paper parameter estimates plot Poisson predictions probability probit problem procedure quasi-likelihood Rasch model regression models response variable sample scale score specified standard errors statistical modelling structure summary statistics symmetric transformation treatment values variance function vector weighted zero