[R] glmpath error

2007-09-19 Thread Tirthadeep
Hi, I am using glampath package for L1 regularized logistic regression. I got the following error messege. > model.fit <- glmpath(train.data[,1:20], train.data$RES, family=binomial) Error in one %*% x : requires numeric matrix/vector arguments where train.data is a 700X21 matrix and 21st colum

Re: [R] glmpath error

2007-09-19 Thread Duncan Murdoch
Tirthadeep wrote: > Hi, > > I am using glampath package for L1 regularized logistic regression. I got > the following error messege. > > >> model.fit <- glmpath(train.data[,1:20], train.data$RES, family=binomial) >> > Error in one %*% x : requires numeric matrix/vector arguments > > where t

Re: [R] glmpath error

2007-09-19 Thread Tirthadeep
Then what is the solution? Duncan Murdoch-2 wrote: > > Tirthadeep wrote: >> Hi, >> >> I am using glampath package for L1 regularized logistic regression. I got >> the following error messege. >> >> >>> model.fit <- glmpath(train.data[,1:20], train.data$RES, family=binomial) >>> >> Err

Re: [R] glmpath error

2007-09-19 Thread Duncan Murdoch
On 9/19/2007 7:46 AM, Tirthadeep wrote: > Then what is the solution? The same method you used for the other columns: train.data[,21] Duncan Murdoch > > > > > Duncan Murdoch-2 wrote: >> >> Tirthadeep wrote: >>> Hi, >>> >>> I am using glampath package for L1 regularized logistic regression.

Re: [R] glmpath error

2007-09-19 Thread Peter Ehlers
Is train.data a *numeric* matrix? Peter Ehlers Tirthadeep wrote: > Then what is the solution? > > > > > Duncan Murdoch-2 wrote: >> Tirthadeep wrote: >>> Hi, >>> >>> I am using glampath package for L1 regularized logistic regression. I got >>> the following error messege. >>> >>> model

Re: [R] glmpath error

2007-09-19 Thread Prof Brian Ripley
On Wed, 19 Sep 2007, Duncan Murdoch wrote: > On 9/19/2007 7:46 AM, Tirthadeep wrote: >> Then what is the solution? > > The same method you used for the other columns: > > train.data[,21] However, the error message is about the first argument (x) and not NULL for the second argument (and applying