Hello Arun. Can you provide some data? To help you better i will need a
complete reproducible example ok?
On Thu, Sep 5, 2013 at 1:49 PM, arun <smartpink...@yahoo.com> wrote:
> HI,
> May be this helps:
> set.seed(28)
> dat1<-
> setNames(as.data.frame(matrix(sample(1:40,10*5,replace=TRUE),ncol=5)),letters[1:5])
> indx<-as.data.frame(combn(names(dat1),2),stringsAsFactors=FALSE)
> res<-t(sapply(indx,function(x)
> {x1<-cbind(dat1[x[1]],dat1[x[2]]);summary(lm(x1[,1]~x1[,2]))$coef[,4]}))
> rownames(res)<-apply(indx,2,paste,collapse="_")
> colnames(res)[2]<- "Coef1"
> head(res,3)
> # (Intercept) Coef1
> #a_b 0.39862676 0.8365606
> #a_c 0.02427885 0.6094141
> #a_d 0.37521423 0.7578723
>
>
> #permutation
> indx2<-expand.grid(names(dat1),names(dat1),stringsAsFactors=FALSE)
> #or
> indx2<- expand.grid(rep(list(names(dat1)),2),stringsAsFactors=FALSE)
> indx2New<- indx2[indx2[,1]!=indx2[,2],]
> res2<-t(sapply(seq_len(nrow(indx2New)),function(i) {x1<- indx2New[i,];
> x2<-cbind(dat1[x1[,1]],dat1[x1[,2]]);summary(lm(x2[,1]~x2[,2]))$coef[,4]}))
> row.names(res2)<-apply(indx2New,1,paste,collapse="_")
> colnames(res2)<- colnames(res)
>
>
> A.K.
>
>
> Hi everyone,
>
> First off just like to say thanks to everyone´s contributions.
> Up until now, I´ve never had to post as I´ve always found the answers
> from trawling through the database. I´ve finally managed to stump
> myself, and although for someone out there, I´m sure the answer to my
> problem is fairly simple, I, however have spent the whole day infront of
> my computer struggling. I know I´ll probably get an absolute ribbing
> for making a basic mistake, or not understanding something fully, but
> I´m blind to the mistake now after looking so long at it.
>
> What I´m looking to do, is formulate a matrix ([28,28]) of
> p-values produced from running linear regressions of 28 variables
> against themselves (eg a~b, a~c, a~d.....b~a, b~c etc...), if that makes
> sense. I´ve managed to get this to work if I just input each variable
> by hand, but this isn´t going to help when I have to make 20 matrices.
>
> My script is as follows;
>
>
> for (j in [1:28])
> {
> ##This section works perfectly, if I don´t try to loop it, I know
> this wont work at the moment, because I haven´t designated what j is,
> but I´m showing to highlight what I´m attempting to do.
>
>
> models <- lapply(varlist, function(x) {
> lm(substitute(ANS ~ i, list(i = as.name(x))), data = con.i)
> })
>
> abc<- lapply(models, function(f) summary(f)$coefficients[,4])
>
> abc<- do.call(rbind, abc)
>
>
>
> }
>
> I get the following error when I try to loop it...
>
> Error in model.frame.default(formula = substitute(j ~ i, list(i =
> as.name(x))),
> :
> variable lengths differ (found for 'ANS') ##ÄNS being my first variable
>
> All variables are of the same length, with 21 recordings for each
>
>
> If anyone can suggest a method of looping, or another means
> or producing ´models´ for each of my 28 variables, without having to do
> it by hand that would be fantastic.
>
> Thanks in advance!!
>
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
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