logspace.utils {statnet.common} | R Documentation |
Utilities for performing calculations on logarithmic scale.
Description
A small suite of functions to compute sums, means, and weighted means on logarithmic scale, minimizing loss of precision.
Usage
log_sum_exp(logx, use_ldouble = FALSE)
log_mean_exp(logx, use_ldouble = FALSE)
lweighted.mean(x, logw)
lweighted.var(x, logw)
lweighted.cov(x, y, logw)
Arguments
logx |
Numeric vector of |
use_ldouble |
Whether to use |
x , y |
Numeric vectors or matrices of |
logw |
Numeric vector of |
Value
The functions return the equivalents of the R expressions given below, but faster and with less loss of precision.
Functions
-
log_sum_exp()
:log(sum(exp(logx)))
-
log_mean_exp()
:log(mean(exp(logx)))
-
lweighted.mean()
: weighted mean ofx
:sum(x*exp(logw))/sum(exp(logw))
forx
scalar andcolSums(x*exp(logw))/sum(exp(logw))
forx
matrix -
lweighted.var()
: weighted variance ofx
:crossprod(x-lweighted.mean(x,logw)*exp(logw/2))/sum(exp(logw))
-
lweighted.cov()
: weighted covariance betweenx
andy
:crossprod(x-lweighted.mean(x,logw)*exp(logw/2), y-lweighted.mean(y,logw)*exp(logw/2))/sum(exp(logw))
Author(s)
Pavel N. Krivitsky
Examples
x <- rnorm(1000)
stopifnot(all.equal(log_sum_exp(x), log(sum(exp(x))), check.attributes=FALSE))
stopifnot(all.equal(log_mean_exp(x), log(mean(exp(x))), check.attributes=FALSE))
logw <- rnorm(1000)
stopifnot(all.equal(m <- sum(x*exp(logw))/sum(exp(logw)),lweighted.mean(x, logw)))
stopifnot(all.equal(sum((x-m)^2*exp(logw))/sum(exp(logw)),
lweighted.var(x, logw), check.attributes=FALSE))
x <- cbind(x, rnorm(1000))
stopifnot(all.equal(mx <- colSums(x*exp(logw))/sum(exp(logw)),
lweighted.mean(x, logw), check.attributes=FALSE))
stopifnot(all.equal(crossprod(t(t(x)-mx)*exp(logw/2))/sum(exp(logw)),
lweighted.var(x, logw), check.attributes=FALSE))
y <- cbind(x, rnorm(1000))
my <- colSums(y*exp(logw))/sum(exp(logw))
stopifnot(all.equal(crossprod(t(t(x)-mx)*exp(logw/2), t(t(y)-my)*exp(logw/2))/sum(exp(logw)),
lweighted.cov(x, y, logw), check.attributes=FALSE))
stopifnot(all.equal(crossprod(t(t(y)-my)*exp(logw/2), t(t(x)-mx)*exp(logw/2))/sum(exp(logw)),
lweighted.cov(y, x, logw), check.attributes=FALSE))