[R] FW: lasso regression

[Gavin Simpson]

On Tue, 2011-07-12 at 10:12 -0400, Heiman, Thomas J. 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!!

Row 1 contains character data, the variable names. Are you missing a
`header = TRUE` (this is the default in `read.csv()`), or do you have
several header lines?

I also think you have the response/predictors back to front there;
otherwise, why would you need to shrink the coefficient and select from
a model with a single predictor?

HTH

G

> Sincerely,
> 
> tom
> 
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