lsum | R Documentation |
Properly compute \log(x_1 + \ldots + x_n)
.
for given log(x_1),..,log(x_n)
. Here, x_i > 0
for all i
.
If the inputs are denoted l_i = log(x_i)
for i = 1,2,..,n
, we
compute log(sum(exp(l[])))
, numerically stably.
Simple vector version of copula:::lsum()
(CRAN package
copula).
lsum(lx, l.off = max(lx))
lx |
n-vector of values log(x_1),..,log(x_n). |
l.off |
the offset to substract and re-add; ideally in the order of the maximum of each column. |
log(x_1 + .. + x_n) = log(sum(x)) = log(sum(exp(log(x)))) =
= log(exp(log(x_max))*sum(exp(log(x)-log(x_max)))) =
= log(x_max) + log(sum(exp(log(x)-log(x_max))))) =
= lx.max + log(sum(exp(lx-lx.max)))
Originally, via paired programming: Marius Hofert and Martin Maechler.
lssum()
which computes a sum in log scale
with specified (typically alternating) signs.
## The "naive" version :
lsum0 <- function(lx) log(sum(exp(lx)))
lx1 <- 10*(-80:70) # is easy
lx2 <- 600:750 # lsum0() not ok [could work with rescaling]
lx3 <- -(750:900) # lsum0() = -Inf - not good enough
m3 <- cbind(lx1,lx2,lx3)
lx6 <- lx5 <- lx4 <- lx3
lx4[149:151] <- -Inf ## = log(0)
lx5[150] <- Inf
lx6[1] <- NA_real_
m6 <- cbind(m3,lx4,lx5,lx6)
stopifnot(exprs = {
all.equal(lsum(lx1), lsum0(lx1))
all.equal((ls1 <- lsum(lx1)), 700.000045400960403, tol=8e-16)
all.equal((ls2 <- lsum(lx2)), 750.458675145387133, tol=8e-16)
all.equal((ls3 <- lsum(lx3)), -749.541324854612867, tol=8e-16)
## identical: matrix-version <==> vector versions
identical(lsum(lx4), ls3)
identical(lsum(lx4), lsum(head(lx4, -3))) # the last three were -Inf
identical(lsum(lx5), Inf)
identical(lsum(lx6), lx6[1])
identical((lm3 <- apply(m3, 2, lsum)), c(lx1=ls1, lx2=ls2, lx3=ls3))
identical(apply(m6, 2, lsum), c(lm3, lx4=ls3, lx5=Inf, lx6=lx6[1]))
})
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