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simplify the normalization in gpdfit #187

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Merged
jgabry merged 2 commits into from
Oct 7, 2021
Merged

simplify the normalization in gpdfit #187

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bffab8c
simplify the normalization in gpdfit, thanks to Seth Axen
avehtari Sep 20, 2021
6b87ccb
Update NEWS.md
jgabry Sep 21, 2021
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6 changes: 6 additions & 0 deletions NEWS.md
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Original file line number Diff line number Diff line change
@@ -1,5 +1,11 @@
# Items for next release go here

* Speed improvement from simplifying the normalization when fitting the
generalized Pareto distribution. (#187, @sethaxen)

* Fixed bug where attribute storing normalizing constant of PSIS weights wasn't
updated when using moment matching. (#167, @fweber144)

* Switch unit tests from Travis to GitHub Actions. (#164)

### Bug fixes
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4 changes: 1 addition & 3 deletions R/gpdfit.R
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Expand Up @@ -40,9 +40,7 @@ gpdfit <- function(x, wip = TRUE, min_grid_pts = 30, sort_x = TRUE) {
xstar <- x[floor(N / 4 + 0.5)] # first quartile of sample
theta <- 1 / x[N] + (1 - sqrt(M / (jj - 0.5))) / prior / xstar
l_theta <- N * lx(theta, x) # profile log-lik
w_theta <- 1 / vapply(jj, FUN.VALUE = numeric(1), FUN = function(j) {
sum(exp(l_theta - l_theta[j]))
})
w_theta <- exp(l_theta - matrixStats::logSumExp(l_theta)) # normalize
theta_hat <- sum(theta * w_theta)
k <- mean.default(log1p(-theta_hat * x))
sigma <- -k / theta_hat
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