[R] Repeated cross-validation for a lm object

[mxkuhn]

The train function in the caret package will do this. The trainControl function would use method ="repeatedcv" and repeats = 100. 

On Feb 18, 2012, at 2:15 PM, Greg Snow <538280 at gmail.com> wrote:

> The validate function in the rms package can do cross validation of
> ols objects (ols is similar to lm, but with additional information),
> the default is to do bootstrap validation, but you can specify
> crossvalidation instead.
> 
> On Thu, Feb 16, 2012 at 10:44 AM, samuel-rosa
> <alessandrosamuel at yahoo.com.br> wrote:
>> Dear R users
>> 
>> I'd like to hear from someone if there is a function to do a repeated k-fold
>> cross-validation for a lm object and get the predicted values for every
>> observation. The situation is as follows:
>> I had a data set composed by 174 observations from which I sampled randomly
>> a subset composed by 150 observations. With the subset (n = 150) I fitted
>> the model: y = a + bx. The model validation has to be done using a repeated
>> k-fold cross-validation on the complete data set (n = 174). I need to use 10
>> folds and repeat the cross-validation 100 times. In the end of the
>> procedure, I need to have access to the predicted values for each
>> observation, that is, to the 100 predicted values for each observation. The
>> function lmCV() in the package chemometrics provides the predicted values.
>> However, it works only with multiple linear regression models.
>> I hope there is a way of doing it.
>> Best regards,
>> 
>> -----
>> Bc.Sc.Agri. Alessandro Samuel-Rosa
>> Postgraduate Program in Soil Science
>> Federal University of Santa Maria
>> Av. Roraima, nº 1000, Bairro Camobi, CEP 97105-970
>> Santa Maria, Rio Grande do Sul, Brazil
>> --
>> View this message in context: http://r.789695.n4.nabble.com/Repeated-cross-validation-for-a-lm-object-tp4394833p4394833.html
>> Sent from the R help mailing list archive at Nabble.com.
>> 
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> 
> 
> 
> -- 
> Gregory (Greg) L. Snow Ph.D.
> 538280 at gmail.com
> 
> ______________________________________________
> R-help at 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.