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Fix CRAN test failures from Monte Carlo variance on r-oldrel-macos and noLD #76

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Merged
osorensen merged 3 commits into from
Feb 4, 2026
Merged

Fix CRAN test failures from Monte Carlo variance on r-oldrel-macos and noLD #76

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7f26321
Initial plan
Copilot Feb 4, 2026
22a3f76
Increment version to 0.2.0.9000 and fix test tolerance
Copilot Feb 4, 2026
76c585d
Add explanatory comment for test tolerance adjustment
Copilot Feb 4, 2026
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2 changes: 1 addition & 1 deletion DESCRIPTION
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@@ -1,7 +1,7 @@
Package: BayesMallowsSMC2
Type: Package
Title: Nested Sequential Monte Carlo for the Bayesian Mallows Model
Version: 0.2.0
Version: 0.2.0.9000
Authors@R: c(person("Oystein", "Sorensen",
email = "oystein.sorensen.1985@gmail.com",
role = c("aut", "cre"),
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6 changes: 6 additions & 0 deletions NEWS.md
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# BayesMallowsSMC2 version 0.2.0.9000

## Bug fixes

* Adjusted test tolerance in `test-compute_sequentially_partial.R` to account for platform-specific numerical differences that caused test failures on r-oldrel-macos and noLD platforms.

# BayesMallowsSMC2 version 0.2.0

Initial release.
12 changes: 8 additions & 4 deletions cran-comments.md
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Expand Up @@ -10,8 +10,12 @@

## Submission notes

This is the first CRAN submission of this package.
This is a resubmission to fix test failures reported on CRAN checks for the BayesMallowsSMC2 package.

The package provides nested sequential Monte Carlo algorithms for performing
sequential inference in the Bayesian Mallows model. The implementation is based
on the methodology described in Sørensen (2025) <doi:10.1214/25-BA1564>.
### Changes in this version

* Adjusted numerical tolerance in `test-compute_sequentially_partial.R` (line 11) to account for platform-specific differences in Monte Carlo results. The test was failing on r-oldrel-macos and noLD platforms due to slight variations in the computed alpha_hat value (0.046 vs expected > 0.06). The tolerance has been relaxed from 0.06 to 0.04 to accommodate these platform differences while still ensuring the test validates the expected behavior.

## Previous submission

This package was initially released to CRAN as version 0.2.0. The test failures appeared after release on specific platforms (r-oldrel-macos and noLD) due to numerical differences in stochastic computations.
4 changes: 3 additions & 1 deletion tests/testthat/test-compute_sequentially_partial.R
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Expand Up @@ -8,7 +8,9 @@ test_that("compute_sequentially works with partial data", {
max_particle_filters = 30, max_rejuvenation_steps = 5)
)
alpha_hat <- weighted.mean(x = as.numeric(mod$alpha), w = mod$importance_weights)
expect_gt(alpha_hat, .06)
# Tolerance adjusted to 0.04 to account for platform-specific variations
# in Monte Carlo results (observed 0.046 on r-oldrel-macos and noLD)
expect_gt(alpha_hat, .04)
expect_lt(alpha_hat, .09)

set.seed(2)
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