On 18.10.2011 11:03, arunkumar1111 wrote:
Hi
I'm performing a PLS
This is my data present in a file
Year Y X2 X3 X4 X5 X6
1960 27.8 397.5 42.2 50.7 78.3 65.8
1960 29.9 413.3 38.1 52 79.2 66.9
1961 29.8 439.2 40.3 54 79.2 67.8
1961 30.8 459.7 39.5 55.3 79.2 69.6
1962 31.2 492.9 37.3 54.7 77.4 68.7
My R-code
Data<- read.csv("C:/TestData.csv")
variable=names(Data)[4:8]
There are only 7 columns in your data.
dataset=NULL
dataset$X=NULL
Why NULL?
len=length(variable)
for( i in 1:len)
Better: for(i in seq_along(variable))
{
var=variable[i]
if(i==1)
{
dataset$X=as.matrix(Data[var])
}
if(i>1)
{
dataset$X=as.matrix(cbind(dataset$X,Data[var]))
}
}
Or even better, forget about that loop!
X <- as.matrix(Data[,4:8])
seems to be the fast way without any loop - but again, there is no 8th
column in your data.
depVar="Y"
dataset$Y=as.matrix(cbind(Data[depVar]))
What's wrong with
dataset$Y <- Data[,depVar]
pls1=mvr(Y~X,data=dataset,ncomp=4)
Looks like you are talking about the pls package (unstated!)?
Then, just forget everything from before and just read in the data and
apply:
fit1 <- mvr(Y ~ X2 + X3 + X4 + X5 + X6, data=Data, ncomp=4)
you do not need all that preprocessing!
summary(pls1)
I get:
ummary(mvr(Y ~ X2 + X3 + X4 + X5 + X6, data=Data, ncomp=4))
Data: X dimension: 5 5
Y dimension: 5 1
Fit method: kernelpls
Number of components considered: 4
TRAINING: % variance explained
1 comps 2 comps 3 comps 4 comps
X 99.73 99.85 100.00 100
Y 78.51 99.81 99.98 100
Uwe Ligges
On execution the error is
Error in get(as.character(FUN), mode = "function", envir = envir) :
object 'X6' of mode 'function' was not found
Please help me on this
--
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and provide commented, minimal, self-contained, reproducible code.
