[R] GLM Question

The minimum achievable level of significance is defined asthe minimum of Prob(Y=y) over all y's. If I have GLM with a treatment and replicate and I would like to find out how to compute the minimum achievable level of significance for that GLM in R For example, how do I do this for the following d

Re: [R] GLM question

to do the prediction for the hold-out data. Is there any better way for cross-validation to learn a model on training data and test it on test data in R? Thanks, Andra --- On Mon, 8/22/11, Joshua Wiley wrote: > From: Joshua Wiley > Subject: Re: [R] GLM question > To: "And

Re: [R] GLM question

Hi Andra, There are several problems with what you are doing (by the way, I point them out so you can learn and improve, not to be harsh or rude). The good news is there is a solution (#3) that is easier than what you are doing right now! 1) glm.fit() is a function so it is a good idea not to us

[R] GLM question

Hi All, I am trying to fit my data with glm model, my data is a matrix of size n*100. So, I have n rows and 100 columns and my vector y is of size n which contains the labels (0 or 1) My question is: instead of manually typing the model as glm.fit = glm(y~ x[,1]+x[,2]+...+x[,100], family=bino

Re: [R] GLM Question

Peter Flom schrieb: What do you mean by "better"? Dear Peter Thank you for your kind respons as well. You are right, we are in constant debate whether it makes sense to remove variables (no matter whether significant or not) from a total dataset which in itself has a certain meaning and may no

Re: [R] GLM Question

Knut Krueger wrote > >I think this is more an general question to GLMs. > >The result was better in all prior GLMs when I admitted the non >significant factors, but this is the first time that the result is worse >than before. What could be the reason for that? > >glm(data1~data2+data3+data4+data5

[R] GLM Question

Hi to all I think this is more an general question to GLMs. The result was better in all prior GLMs when I admitted the non significant factors, but this is the first time that the result is worse than before. What could be the reason for that? glm(data1~data2+data3+data4+data5+data6,family="ga