lsei (version 1.2-0)

hfti: Least Squares Solution using Householder Transformation

Description

Solves the least squares problem using Householder forward triangulation with column interchanges. It is an R interface to the HFTI function that is described in Lawson and Hanson (1974, 1995). Its Fortran implementation is public domain and is available at http://www.netlib.org/lawson-hanson.

Usage

hfti(a, b, tol=1e-7)

Arguments

a

Design matrix.

b

Response vector or matrix.

tol

Tolerance for determining the pseudorank.

Value

b

first krank elements contains the solution

krank

psuedo-rank

rnorm

Euclidean norm of the residual vector.

Details

Given matrix a and vector b, hfti solves the least squares problem:

$$\mathrm{minimize\ \ } || a x - b ||.$$

References

Lawson and Hanson (1974, 1995). Solving least squares problems. Englewood Cliffs, N.J., Prentice-Hall.

See Also

lsei, nnls.

Examples

Run this code
# NOT RUN {
a = matrix(rnorm(10*4), nrow=10)
b = a %*% c(0,1,-1,1) + rnorm(10)
hfti(a, b)
# }

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