Titlebook: Robust Diagnostic Regression Analysis; Anthony Atkinson,Marco Riani Book 2000 Springer Science+Business Media New York 2000 Generalized li

colloquial

Regression and the Forward Search,uction of some score tests for regression models, particularly that for transformations in Chapter 4. Related results are needed for testing the goodness of the link in a generalized linear model, Chapter 6. Several of the quantities monitored during the forward search come from considering the effe

過于光澤

Regression,sked outliers and so provide difficulties for least squares diagnostics based on backwards deletion. We show that the data do indeed present such problems, but that our procedure finds the hidden structure.

Diluge

Transformations to Normality,of the data. For the introductory example of the wool data in Chapter 1, the normal plot of residuals in Figure 1.9 is improved by working with log y rather than y ( Figure 4.2). The transformation improves the approximate normality of the errors. The transformation also improves the homogeneity of

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高度

Generalized Linear Models,proximately so by transformation. This chapter extends the class of models for the forward search to include generalized linear models. We give examples in which the errors of observation have the gamma distribution. For this continuous distribution the results are similar to those for the normal di

reflection

分發(fā)

The Production of Crayfish Tailflip Escape Responses, water away from danger. Aspects of the behavioral and neural analysis of this tailflip escape behavior are the subject of this essay. Since a comprehensive and systematic treatment of the same topic has recently been published in ., Vol. 4 (Wine and Krasne, 1982), we here emphasize recent advances and discuss interpretations of them.