RE: [R] "mvr" function

From: McGehee, Robert <Robert.McGehee_at_geodecapital.com>
Date: Thu 02 Jun 2005 - 09:14:03 EST


Jim,
I had some of the same difficulties. The NIR data frame consists of a column of y variables and a matrix of X variables (and until looking at this dataset, I had not realized that data frames could hold matrices). So, after consulting the R-help sages, I turned by data into an identical structure using something like this:

dataSet <- data.frame(y = vol[, 12])
dataSet$X <- data.matrix(vol[, 1:11])

ans.pcr <- pcr(y ~ X, 6, data = dataSet, validation = "CV")

If there's a more elegant way of doing this without using data frames of matrices, I'd be interested as well.

HTH,
Robert

-----Original Message-----
From: Jim BRINDLE [mailto:j_brindle@hotmail.com] Sent: Wednesday, June 01, 2005 5:03 PM
To: r-help@stat.math.ethz.ch
Subject: [R] "mvr" function

Hello,

I am trying to understand how to utilize the "mvr" function in the pls Package of R. I am utilizing the R "pls Package" document dated 18 May 2005
as guidance. My data set consists of a 12 x 12 data frame created from reading in a table of values. I have read the data in via the command:

volumes <- read.table("THA_vol.txt", header = TRUE)

and then created a data.frame called "vol". My response variable is in the
last column of the "vol" data frame and my dependent variables are in columns 1 through 11.

To familiarize myself with this approach I have utilized the NIR data set
(included in the pls Package). I get the following command to work with the
NIR data set:

NIR.pcr <- pcr(y ~ X,6,data=NIR,validation="CV")

However, when I run the following script which effectively substitutes my
data set (& modify variable names accordingly) into the above equation:

y <- vol[,12]
X <- vol[,1:11]
ans.pcr <- pcr(y ~ X,6,data=vol,validation="CV")

I get the following error:

Error in model.frame(formula, rownames, variables, varnames, extras, extranames, :

       invalid variable type

I have looked at the NIR data set in the pls Package and tried to see how it
"structurally" differs from my data-set "structure" (other than in its size).

Does anyone have any insight they might be willing to share?

Thank you kindly.


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R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Thu Jun 02 09:21:21 2005

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