Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Trying not to fall into Thanksgiving Day, football, coma.  So I started looking at the Matrix package.

Started out by changing my code from before to create a matrix using the Matrix() function from the Matrix package.
n = 4000
c = Matrix(.9,n,n)
for(i in 1:n){
c[i,i] = 1;
}
That took… a LONG time. What the hell?  Reading the intro document, it looks like there are multiple internal classes that hold matrices.  I’m guessing that every time I update the matrix it tries to decide what class should be used.  That could make doing matrix operations, painful.

This however works MUCH faster — probably because the matrix is only checked once on creation.
n = 4000
c = matrix(.9,n,n)
for(i in 1:n){
c[i,i] = 1
}
c = Matrix(c)
What does the internal structure of this look like?
str(c)

Formal class ‘dsyMatrix’ [package “Matrix”] with 5 slots
[email protected] x       : num [1:16000000] 1 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 …
[email protected] Dim     : int [1:2] 4000 4000
[email protected] Dimnames:List of 2
.. ..$: NULL .. ..$ : NULL
[email protected] uplo    : chr “U”
[email protected] factors : list()
The document referenced above lists a dsyMatrix as “Symmetric real matrices in non-packed storage.” There is a type “dpoMatrix Positive semi-de nite symmetric real matrices in non-packed storage.” Technically, this matrix is PSD. Why is it not a dpoMatrix?

Let’s recalculate the Cholesky, look at the performance, and re-check the class:
gflops = function(ops,time){
fps = ops/time
return(fps/1000000000)
}

start = Sys.time()
root = chol(c)
end = Sys.time()
gflops(n^3/3,as.numeric(end – start))
 1.584472
str(c)
Formal class ‘dsyMatrix’ [package “Matrix”] with 5 slots
[email protected] x       : num [1:16000000] 1 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 …
[email protected] Dim     : int [1:2] 4000 4000
[email protected] Dimnames:List of 2
.. ..$: NULL .. ..$ : NULL
[email protected] uplo    : chr “U”
[email protected] factors :List of 1
.. ..$Cholesky:Formal class ‘Cholesky’ [package “Matrix”] with 5 slots .. .. .. [email protected] x : num [1:16000000] 1 0 0 0 0 0 0 0 0 0 … .. .. .. [email protected] Dim : int [1:2] 4000 4000 .. .. .. [email protected] Dimnames:List of 2 .. .. .. .. ..$ : NULL
.. .. .. .. ..$: NULL .. .. .. [email protected] uplo : chr “U” .. .. .. [email protected] diag : chr “N” str(root) Formal class ‘Cholesky’ [package “Matrix”] with 5 slots [email protected] x : num [1:16000000] 1 0 0 0 0 0 0 0 0 0 … [email protected] Dim : int [1:2] 4000 4000 [email protected] Dimnames:List of 2 .. ..$ : NULL
.. ..\$ : NULL
[email protected] uplo    : chr “U”
[email protected] diag    : chr “N”

Matrix class didn’t change and the performance is worse than the base class.

Notice how the Cholesky root is stored on the c matrix? This means we can get back to it if needed. That’s pretty cool.

Unfortunately, the chol() function in Matrix and base requires a positive definite (PD) matrix.  Often in finance, I only have positive semi-definite (PSD) matrices.  We’ll talk about that next time.