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Fix for edge case when likelihood is infinite when profiling #72

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Nov 9, 2023
Merged

Fix for edge case when likelihood is infinite when profiling #72

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c8a8089
Handling edge case when likelihood is infinite during profiling. Prev…
Nov 9, 2023
6527620
Adding unit tests for check for infinite (and NaN) likelihood values
Nov 9, 2023
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13 changes: 7 additions & 6 deletions R/ModelFit.R
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Original file line number Diff line number Diff line change
Expand Up @@ -937,21 +937,22 @@ getCyclopsProfileLogLikelihood <- function(object,
while (length(grid) != 0) {
ll <- fixedGridProfileLogLikelihood(object, parm, grid, includePenalty)
profile <- bind_rows(profile, ll) %>% arrange(.data$point)

if (any(is.nan(profile$value))) {
if (all(is.nan(profile$value))) {
invalid <- is.nan(profile$value) | is.infinite(profile$value)
if (any(invalid)) {
if (all(invalid)) {
warning("Failing to compute likelihood at entire initial grid.")
return(NULL)
}

start <- min(which(!is.nan(profile$value)))
end <- max(which(!is.nan(profile$value)))
start <- min(which(!invalid))
end <- max(which(!invalid))
if (start == end) {
warning("Failing to compute likelihood at entire grid except one. Giving up")
return(NULL)
}
profile <- profile[start:end, ]
if (any(is.nan(profile$value))) {
invalid <- invalid[start:end]
if (any(invalid)) {
warning("Failing to compute likelihood in non-extreme regions. Giving up.")
return(NULL)
}
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28 changes: 28 additions & 0 deletions tests/testthat/test-profileLikelihood.R
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Expand Up @@ -97,3 +97,31 @@ start, length, event, x1, x2
expect_equal(coef(fit)["x1"], argMax)
})

test_that("Check adapative profiling likelihood, other covariate is perfect predictor", {

test <- read.table(header=T, sep = ",", text = "
start, length, event, x1, x2
0, 4, 1,0,1
0, 4,1,2,1
0, 4, 0,0,0
0, 4,1,0,1
0, 4, 1,1,1
0, 4,0,1,0
0, 4, 1,1,1
")
data <- createCyclopsData(event ~ x1 + x2, data = test,
modelType = "cpr")

# Recreating combination of circumstances that lead to infinite log likelihood
# Note: infinite variance would have been selected by cross-validation if we had enough data:
fit <- fitCyclopsModel(data,
prior = createPrior("laplace", variance = Inf, exclude = "x1"))
expect_warning(getCyclopsProfileLogLikelihood(fit, "x1", bounds = c(0, 2), initialGridSize = 10),
"Failing to compute likelihood at entire initial grid")

# This just produces NaN likelihood:
fit <- fitCyclopsModel(data)
expect_warning(getCyclopsProfileLogLikelihood(fit, "x1", bounds = c(0, 2), initialGridSize = 10),
"Failing to compute likelihood at entire initial grid")
})