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⚡ Bolt: [performance improvement] Cache inverted matrices in vuongtest #28

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⚡ Bolt: [performance improvement] Cache inverted matrices in vuongtest #28

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⚡ Bolt: Cache inverted matrices in vuongtest
seonghobae Jul 5, 2026
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⚡ Bolt: Cache inverted matrices in vuongtest
seonghobae Jul 5, 2026
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⚡ Bolt: Cache inverted matrices in vuongtest
seonghobae Jul 5, 2026
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⚡ Bolt: Cache inverted matrices in vuongtest
seonghobae Jul 5, 2026
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3 changes: 3 additions & 0 deletions .jules/bolt.md
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## 2024-05-18 - Caching Matrix Inversions in vuongtest
**Learning:** In statistical R packages involving likelihood calculations, matrix inversion is a common performance bottleneck. Repeating the exact same inversion inside matrix bindings multiplies this cost unnecessarily.
**Action:** Always inspect matrix construction blocks for duplicated expensive operations and extract them into cached local variables before assembling the final block matrix.
11 changes: 7 additions & 4 deletions R/vuongtest.R
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Expand Up @@ -271,10 +271,13 @@ calcLambda <- function(object1, object2, n, score1, score2, vc1, vc2) {
AB2 <- calcAB(object2, n, score2, vc2)
Bc <- calcBcross(AB1$sc, AB2$sc, n)

W <- cbind(rbind(-AB1$B %*% chol2inv(chol(AB1$A)),
t(Bc) %*% chol2inv(chol(AB1$A))),
rbind(-Bc %*% chol2inv(chol(AB2$A)),
AB2$B %*% chol2inv(chol(AB2$A))))
# Bolt: cache matrix inversions to avoid recalculating the O(n^3) inverse twice for each model
invA1 <- chol2inv(chol(AB1$A))
invA2 <- chol2inv(chol(AB2$A))
W <- cbind(rbind(-AB1$B %*% invA1,
t(Bc) %*% invA1),
rbind(-Bc %*% invA2,
AB2$B %*% invA2))

lamstar <- eigen(W, only.values=TRUE)$values
## Discard imaginary part, as it only occurs for tiny eigenvalues?
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