[R] Expressing a multinomial GLM as a series of binomial GLMs

Dear all, I am trying to express a multinomial GLM (using nnet) as a series of GLM models. However, when I compare the multinom() predictions to those from GLM, I see differences that I can´t explain. Can anyone help me out here? Here comes a reproducible example: ## # set up data: (don´t care

[R] OrchardSprays reference

Dear all, Does anyone have a PDF of the classic OrchardSprays reference (data(OrchardSprays)): C. G. Butler, D. J. Finney, P. Schiele (1943) Experiments on the poisoning of honeybees by insecticidal and fungicidal sprays used in orchards. Ann Appl Biol 30:143–150. Thanks very much and best wis

Re: [R] interaction.plot for continuous variables

you can also use equal.count() from lattice to split up your continuous variables, then enter them as conditioning variables eg in xyplot() Von: r-help-boun...@r-project.org [r-help-boun...@r-project.org]" im Auftrag von "Greg Snow [538...@gmail.com] Gesen

Re: [R] Self-starting nonlinear power law function

Dear all, I have just written the self-starting power law function myself. Here it is: ## # Self-starting power law function written by C. Scherber powermodel=function(x,a,b,c) {a+b*x^c} powermodelInit=function(mCall,LHS,data){ xy=sortedXyData(mCall[["x"]],LHS,data) lmFit1=lm(xy[,"y"]~1) #for "

[R] Self-starting nonlinear power law function

Dear all, Has anyone written a self-starting power law function of the form mypower=function(x,a,b,c){a+b*x^c} ? Or is there a nonlinear regression package containing more selfStart() functions than nlme? Thank you very much for your help! Best wishes Christoph [running R 3.0.1 on Windows 7