Yes, computing WB.%*%t(WB) may be the problem, by either method.
if the goal is to compute the inverse of WB%*%t(WB), you should
consider computing the singular value or QR decomposition for the
matrix WB.
If WB = Q%*%R, where Q is orthogonal, then WB %*% t(WB) =R %*%t(R),
and the inverse of WB%*%t(WB) is inv.t(R)%*% inv.R.
computing (WB) %*% t(WB) squares the condition number of the matrix.
This is similar to the loss of precision that occurs when you compute
the variance via mean(X^2)-mean(X)^2.
albyn
Quoting "dos Reis, Marlon" <marlon.dosr...@agresearch.co.nz>:
Dear All,
I'm preparing a simple algorithm for matrix multiplication for a
specific purpose, but I'm getting some unexpected results.
If anyone could give a clue, I would really appreciate.
Basically what I want to do is a simple matrix multiplication:
(WB) %*% t(WB).
The WB is in the disk so I compared to approaches:
- Load 'WB' using 'read.table' (put it in WB.tmp) and then to the
simple matrix multiplication
WB.tmp%*%t(WB.tmp)
- Scan each row of WB and do the cross products 'sum(WB.i*WB.i)'
and 'sum(WB.i*WB.j)', which proper arrangement leads to WBtWB.
Comparing these two matrices, I get the very similar values, however
when I tried their inverse, WBtWB leads to a singular system.
I've tried different tests and my conclusion is that my precision
problem is related to cross products 'sum(WB.i*WB.i)' and
'sum(WB.i*WB.j)'.
Does it makes sense?
Thanks,
Marlon
WB.tmp%*%t(WB.tmp)
WB.i WB.i WB.i
WB.i 1916061939 2281366606 678696067
WB.i 2281366606 3098975504 1092911209
WB.i 678696067 1092911209 452399849
WBtWB
[,1] [,2] [,3]
[1,] 1916061939 2281366606 678696067
[2,] 2281366606 3098975504 1092911209
[3,] 678696067 1092911209 452399849
WBtWB-WB.tmp%*%t(WB.tmp)
WB.i WB.i WB.i
WB.i 2.861023e-06 4.768372e-07 4.768372e-07
WB.i 4.768372e-07 3.814697e-06 -2.622604e-06
WB.i 4.768372e-07 -2.622604e-06 5.960464e-08
solve(WB.tmp%*%t(WB.tmp))
WB.i WB.i WB.i
WB.i -41692.80 58330.89 -78368.17
WB.i 58330.89 -81608.66 109642.09
WB.i -78368.17 109642.09 -147305.32
solve(WBtWB)
Error in solve.default(WBtWB) :
system is computationally singular: reciprocal condition number =
2.17737e-17
WB.tmp<-NULL
WBtWB<-matrix(NA,n,n)
for (i in 1:n)
{
setwd(Home.dir)
WB.i<-scan("WB.dat", skip = (i-1), nlines = 1)
WB.tmp<-rbind(WB.tmp,WB.i)
WBtWB[i,i]<-sum(WB.i*WB.i)
if (i<n)
{
for (j in (i+1):n)
{
setwd(Home.dir)
WB.j<-scan("WB.dat", skip = (j-1), nlines = 1)
WBtWB[i,j]<-sum(WB.i*WB.j)
WBtWB[j,i]<-sum(WB.i*WB.j)
}
}
}
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