Description Usage Arguments Details Value Benchmarking Author(s) References See Also Examples
Accurately computes the logarithm of the sum of exponentials, that is, log(sum(exp(lx))). If lx = log(x), then this is equivalently to calculating log(sum(x)).
This function, which avoid numerical underflow, is often used when computing the logarithm of the sum of small numbers (|x| << 1) such as probabilities.
1 |
lx |
A |
na.rm |
If |
... |
Not used. |
This is function is more accurate than log(sum(exp(lx)))
when the values of x = exp(lx) are |x| << 1.
The implementation of this function is based on the observation that
log(a + b) = [ la = log(a), lb = log(b) ] = log( exp(la) + exp(lb) ) = la + log ( 1 + exp(lb - la) )
Assuming la > lb, then |lb - la| < |lb|, and it is
less likely that the computation of 1 + exp(lb - la) will
not underflow/overflow numerically. Because of this, the overall
result from this function should be more accurate.
Analoguously to this, the implementation of this function finds the
maximum value of lx
and subtracts it from the remaining values
in lx
.
Returns a numeric
scalar.
This method is optimized for correctness, that avoiding underflowing. It is implemented in native code that is optimized for speed and memory.
Henrik Bengtsson
[1] R Core Team, Writing R Extensions, v3.0.0, April 2013.
[2] Laurent El Ghaoui,
Hyper-Textbook: Optimization Models and Applications,
University of California at Berkeley, August 2012.
(Chapter 'Log-Sum-Exp (LSE) Function and Properties',
https://inst.eecs.berkeley.edu/~ee127a/book/login/def_lse_fcn.html)
[3] R-help thread logsumexp function in R, 2011-02-17.
https://stat.ethz.ch/pipermail/r-help/2011-February/269205.html
To compute this function on rows or columns of a matrix,
see rowLogSumExps
().
For adding two double values in native code, R provides
the C function logspace_add()
[1].
For properties of the log-sum-exponential function, see [2].
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | ## EXAMPLE #1
lx <- c(1000.01, 1000.02)
y0 <- log(sum(exp(lx)))
print(y0) ## Inf
y1 <- logSumExp(lx)
print(y1) ## 1000.708
## EXAMPLE #2
lx <- c(-1000.01, -1000.02)
y0 <- log(sum(exp(lx)))
print(y0) ## -Inf
y1 <- logSumExp(lx)
print(y1) ## -999.3218
## EXAMPLE #3
## R-help thread 'Beyond double-precision?' on May 9, 2009.
set.seed(1)
x <- runif(50)
## The logarithm of the harmonic mean
y0 <- log(1/mean(1/x))
print(y0) ## -1.600885
lx <- log(x)
y1 <- log(length(x)) - logSumExp(-lx)
print(y1) ## [1] -1.600885
# Sanity check
stopifnot(all.equal(y1, y0))
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