Type: | Package |
Title: | Fast Implementation of the Iterative Proportional Fitting Procedure in C |
Version: | 1.0.2 |
Author: | Alexander W Blocker |
Maintainer: | Alexander W Blocker <ablocker@gmail.com> |
Description: | A fast (C) implementation of the iterative proportional fitting procedure. |
License: | Apache License (== 2.0) |
LazyLoad: | yes |
URL: | https://github.com/awblocker/ipfp |
RoxygenNote: | 7.1.2 |
NeedsCompilation: | yes |
Packaged: | 2022-05-04 18:34:18 UTC; rstudio |
Repository: | CRAN |
Date/Publication: | 2022-05-05 06:50:05 UTC |
Function to run IPFP (iterative proportional fitting procedure)
Description
Use IPFP starting from x0 to produce vector x s.t. Ax = y within tolerance. Need to ensure that x0 > 0.
Usage
ipfp(
y,
A,
x0,
tol = sqrt(.Machine$double.eps),
maxit = 1000,
verbose = FALSE,
full = FALSE
)
Arguments
y |
numeric constraint vector (length nrow) |
A |
constraint matrix (nrow x ncol) |
x0 |
numeric initial vector (length ncol) |
tol |
numeric tolerance for IPFP; defaults to
|
maxit |
integer maximum number of iterations for IPFP; defaults to 1e3 |
verbose |
logical parameter to select verbose output from C function |
full |
logical parameter to select full return (with diagnostic info) |
Value
if not full, a vector of length ncol containing solution obtained by IPFP. If full, a list containing solution (as x), the number of iterations (as iter), and the L2 norm of Ax - y (as errNorm)
Examples
A <- matrix(c(1,0,0, 1,0,0, 0,1,0, 0,1,0, 0,0,1), nrow=3)
x <- rgamma(ncol(A), 10, 1/100)
y <- A %*% x
x0 <- x * rgamma(length(x), 10, 10)
ans <- ipfp(y, A, x0, full=TRUE)
print(ans)
print(x)