Hi,
(i) As David suggested, please use `dput` to provide examples of data!
(ii) The nut of your problem is that you are giving lars an object
that it is not expecting. It wants a *matrix* for its `x` variable, as
you'll see in the help for ?lars.
So, as long as this expression:
R> is.numeric(x) && is.matrix(x)
Evaluates to FALSE for your x, you won't get it to work.
(iii) Consider using glmnet -- you get the lass "for free" when you
set a=1, but you can also see if the "elastic net" is helpful.
-steve
On Tue, Jul 12, 2011 at 10:12 AM, Heiman, Thomas J. <thei...@mitre.org> wrote:
>
> Hi,
>
> Hopefully I got the formatting down.. I am trying to do a lasso regression
> using the lars package with the following data (the data files is in .csv
> format):
>
> V1 V2 V3 V4
> V5 V6 V7 V8 V9
> 1 FastestTime WinPercentage PlacePercentage ShowPercentage
> BreakAverage FinishAverage Time7Average Time3Average Finish
> 2 116.9 0.14285715 0.14285715 0.2857143
> 4.428571 3.2857144 117.557144 117.76667 5.0
> 3 116.22857 0.2857143 0.42857143 0.14285715
> 6.142857 2.142857 116.84286 116.8 2.0
> 4 116.41428 0.0 0.14285715 0.2857143
> 5.714286 3.7142856 117.24286 117.166664 4.0
> 5 115.8 0.5714286 0.0 0.2857143
> 2.142857 2.5714285 116.21429 116.53333 6.0
>
> #load Data
> crs<-
> read.csv("file:///C:/temp/Horse//horseracing.csv<file:///C:\temp\Horse\horseracing.csv>",
> na.strings=c(",", "NA", "", "?"), encoding="UTF-8")
>
> # # define x and y
> x= x<-crs[,9] #predictor variables
> y= y<-crs[1:8,] #response variable
>
>
> library(lars)
> cv.lars(x, y, K=10, trace=TRUE, plot.it = TRUE,se = TRUE, type="lasso")
>
> and I get:
>
> LASSO sequence
> Error in one %*% x : requires numeric/complex matrix/vector arguments
>
> Any idea on what I am doing wrong? Thank you!!
>
> Sincerely,
>
> tom
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Steve Lianoglou
Graduate Student: Computational Systems Biology
| Memorial Sloan-Kettering Cancer Center
| Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact
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