Solve {limSolve} | R Documentation |
Generalised inverse solution of
Ax=B
It uses the Moore-Penrose generalized inverse of matrix A (function ginv
from package MASS).
Note: solve
, the R default requires square, positive definite A. Solve does not have this restriction.
Solve(A, B=diag(nrow=nrow(A)), tol=sqrt(.Machine$double.eps))
A |
numeric matrix containing the coefficients of the equation Ax=B |
B |
numeric matrix containing the right-hand sides of the equation; the default is the unity matrix, in which case the function will return the Moore-Penrose generalized inverse of matrix A |
tol |
tolerance for selecting singular values |
a vector with the generalised inverse solution
Karline Soetaert <k.soetaert@nioo.knaw.nl>
ginv
to estimate the Moore-Penrose generalized inverse of a matrix, in package MASS,
solve
the R default
A <- matrix(nrow=4,ncol=3,data=c(1:8,6,8,10,12)) # col3 = col1+col2 B <- 0:3 X <- Solve(A,B) # generalised inverse solution A %*% X - B # should be zero (except for roundoff) (gA <- Solve(A)) # generalised inverse of A