search for: vicvoncastle

Hello all, I am using the clustering functions in R in order to work with large masses of binary time series data, however the clustering functions do not seem able to fit this size of practical problem. Library 'hclust' is good (though it may be sub par for this size of problem, thus doubly poor for this application) in that I do not want to make assumptions about the number of

Begin forwarded message: > From: Ken Hutchison <vicvoncastle@gmail.com> > Date: January 15, 2012 8:54:49 PM EST > To: Ben Bolker <bbolker@gmail.com> > Subject: Re: [R] Trouble installing packages on R2.14.1 > > Check browser proxy settings and run R.exe with the proper flags to use them from cmd. > Hope that helps, > Ken &...

Hello everyone, What is the simplest, most RELIABLE way to import data from MS EXCEL (.xls) format to R? In the past I have used the read.xls() function from the xlsReadWrite package, however, I have been wrestling with it all afternoon long with no success. I continue to receive the following error message: > {widge<-read.xls("F:\\Classes\\Z1.Data\\stat.3010\\WidgeOne.xls", +

Hello, I was using version 2.13.2 and I have just downloaded the latest version 2.14.1. However, I''m trying to install the packages I was using and when I look for them in the packages list, I can´t find many in the CRAN binaries (e.g. "vegan"). I do find them in the CRAN sources but the installation fails. I tried downloading the version 2.14.0 and I had the same problem. I

Hello, I am a new user of R, and I'd be grateful if someone could help me with the following: I would like to compute the mean of variable "trust" in dataframe "foo", but separately for each level of variable V2. That is, I'd like to compute the mean of trust at each level of V2. I have done this: > tmp <- by(foo, foo$V2, function(x) mean(foo$trust, na.rm=T))

Dear R Users Any idea if there exists any one dimensional Cox Process datasets in R? 'Spatstat' is very comprehensive but doesn't seem to have any examples of 1D (time series) Doubly Stochastic Poisson Process data. (I am aware it can be simulated) Thank you, Ken [[alternative HTML version deleted]]

Dear R-List, Is there any way to handle NA's within tree objects themselves in terms of the predict.tree( )? I understand that if there is an NA at a split in a certain variable, the prediction is classified at that node and not dropped further down the tree. Are there any other and possibly more robust ways to handle NAs within tree objects? Note: I only would like information on tree(