PSM (version 0.8-12)

matexp: Matrix exponential

Description

Matrix exponential af a square matrix computed by the pade approximation.

Usage

matexp(a, dt = 1, order = 8)

Arguments

a

A square numeric matrix

dt

Integration Time step

order

Pade approximation order

Value

The matrix exponential is returned. The function issues an error if problems occured in the fortran engine.

Details

This implementation is based on Niels Rode Kristensens work. This package is also highly inspired by David Firth's R package mexp.

References

This implementation is based on Niels Rode Kristensens work. This package is also highly inspired by David Firth's R package mexp.

The examples below are all from David Firth's mexp package but the accuracy example has been removed as this package does not calculate the accuracy.

Niels Rode Kristensen, http://www2.imm.dtu.dk/~ctsm/

Examples

# NOT RUN {
## The test cases have been taken directly from David Firths MEXP package.
##
##
## ----------------------------
## Test case 1 from Ward (1977)
## ----------------------------
test1 <- t(matrix(c(
    4, 2, 0,
    1, 4, 1,
    1, 1, 4), 3, 3))
    
matexp(test1)

## Results on Power Mac G3 under Mac OS 10.2.8
##                    [,1]               [,2]               [,3]
## [1,] 147.86662244637000 183.76513864636857  71.79703239999643
## [2,] 127.78108552318250 183.76513864636877  91.88256932318409
## [3,] 127.78108552318204 163.67960172318047 111.96810624637124
## -- these agree with ward (1977, p608)
##
## A naive alternative to mexp, using spectral decomposition:
mexp2 <- function(matrix){
             z <- eigen(matrix,sym=FALSE)
             Re(z$vectors %*% diag(exp(z$values)) %*%
                    solve(z$vectors))
}

try(mexp2(test1))

## now gives an error from solve !
##
## older result was
##                   [,1]                [,2]               [,3]
##[1,] 147.86662244637003  88.500223574029647 103.39983337000028
##[2,] 127.78108552318220 117.345806155250600  90.70416537273444
##[3,] 127.78108552318226  90.384173332156763 117.66579819582827
## -- hopelessly inaccurate in all but the first column.
##
##
## ----------------------------
## Test case 2 from Ward (1977)
## ----------------------------
test2 <- t(matrix(c(
    29.87942128909879, .7815750847907159, -2.289519314033932,
    .7815750847907159, 25.72656945571064,  8.680737820540137,
   -2.289519314033932, 8.680737820540137,  34.39400925519054),
           3, 3))

matexp(test2)

##                   [,1]               [,2]               [,3]
##[1,]   5496313853692357 -18231880972009844 -30475770808580828
##[2,] -18231880972009852  60605228702227024 101291842930256144
##[3,] -30475770808580840 101291842930256144 169294411240859072
## -- which agrees with Ward (1977) to 13 significant figures
mexp2(test2)
##                   [,1]               [,2]               [,3]
##[1,]   5496313853692405 -18231880972009100 -30475770808580196
##[2,] -18231880972009160  60605228702221760 101291842930249376
##[3,] -30475770808580244 101291842930249200 169294411240850880
## -- in this case a very similar degree of accuracy.
##
## ----------------------------
## Test case 3 from Ward (1977)
## ----------------------------
test3 <- t(matrix(c(
    -131, 19, 18,
    -390, 56, 54,
    -387, 57, 52), 3, 3))
    
matexp(test3)

##                    [,1]                [,2]                [,3]
##[1,] -1.5096441587713636 0.36787943910439874 0.13533528117301735
##[2,] -5.6325707997970271 1.47151775847745725 0.40600584351567010
##[3,] -4.9349383260294299 1.10363831731417195 0.54134112675653534
## -- agrees to 10dp with Ward (1977), p608.

mexp2(test3)

##                   [,1]               [,2]                [,3]
##[1,] -1.509644158796182 0.3678794391103086 0.13533528117547022
##[2,] -5.632570799902948 1.4715177585023838 0.40600584352641989
##[3,] -4.934938326098410 1.1036383173309319 0.54134112676302582
## -- in this case, a similar level of agreement with Ward (1977).
##

# }