sessionInfo()
R version 2.13.1 (2011-07-08)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)
locale:
[1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] Matrix_0.999375-50 lattice_0.19-30
loaded via a namespace (and not attached):
[1] grid_2.13.1 tools_2.13.1
Dear R-help,
I am using the Matrix (0.999375-50) and MatrixModels (0.2-1) packages to
estimate regressions with 14,791 fixed effects. I use the function
sparse.model.matrix() to partial out the fixed effects and then use lm() and an
adjustment to the standard errors to study the four regressors that I am
interested in.
I want to calculate standardized residuals and need the diagonal elements of
the hat matrix. I tried to adjust function hat() in the stats package for use
with sparse matrices. But the method qr.qy does not seem to have a function
available for the following signature: signature(qr = sparseQR, y =
dgCMatrix) - although it indicates that it understands this signature.
Following is a minimal example (in my application dd2 is too large for my
memory):
library(Matrix)
data(KNex);
mm - KNex$mm
mmQR - qr(mm)
dim(mmQR) # 1850 712
class(mmQR) # [1] sparseQR;attr(,package);Matrix
dd1 - sparseMatrix(1:ncol(mm),1:ncol(mm), x = 1, dims = c(nrow(mm),ncol(mm)))
class(dd1) # dgCMatrix;attr(,package);Matrix
dd2 - diag(1,ncol = ncol(mm) , nrow = nrow(mm))
class(dd2) #matrix
showMethods(qr.qy)
#Function: qr.qy (package base)
#qr=ANY, y=ANY
#qr=sparseQR, y=dgCMatrix
#(inherited from: qr=ANY, y=ANY)
#qr=sparseQR, y=dgeMatrix
#qr=sparseQR, y=matrix
#qr=sparseQR, y=numeric
dhat1 - rowSums(qr.qy(qr = mmQR, y = dd1)^2) # Error in rowSums(qr.qy(qr =
mmQR, y = dd1)^2) :
# error in evaluating the argument 'x' in selecting a method for function
'rowSums':
# Error in qr.qy(qr = mmQR, y = dd1) : argument is not a QR decomposition
dhat2 - rowSums(qr.qy(qr = mmQR, y = dd2)^2) # Works fine
I would be grateful for pointers how to add a function for Matrix:::qr.qy and
signature(qr = sparseQR, y = dgCMatrix). What low level functions do I have
to call?
I would also be grateful for any suggestions for finding diagonal values of the
hat matrix in regression problems with large and sparse design matrices.
Best,
Felix Lamp
(Erasmus University Rotterdam, School of Economics)
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