From ebc937dbc187a935ad7d99856a3262640f557afe Mon Sep 17 00:00:00 2001
From: seonghobae <8172694+seonghobae@users.noreply.github.com>
Date: Tue, 23 Jun 2026 04:10:19 +0000
Subject: [PATCH] =?UTF-8?q?=E2=9A=A1=20Bolt:=20Remove=20redundant=20matrix?=
 =?UTF-8?q?=20inversions=20in=20vuongtest.R?=
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Replaced `chol2inv(chol(...))` of an already inverted matrix by passing the non-inverted matrix forward, saving computation time.
---
 .jules/bolt.md |  3 +++
 R/vuongtest.R  | 14 +++++++-------
 2 files changed, 10 insertions(+), 7 deletions(-)
 create mode 100644 .jules/bolt.md

diff --git a/.jules/bolt.md b/.jules/bolt.md
new file mode 100644
index 0000000..043ec34
--- /dev/null
+++ b/.jules/bolt.md
@@ -0,0 +1,3 @@
+## 2024-06-23 - Removed redundant matrix inversions
+**Learning:** Found redundant double inversions of variance-covariance matrices in `vuongtest.R` where `A = chol2inv(chol(tmpvc))` was calculated, and then later `chol2inv(chol(A))` was used, essentially computing `tmpvc` again.
+**Action:** Always check if a variable holding a matrix inverse is inverted again downstream, and refactor to pass the original un-inverted matrix instead to save computation time.
diff --git a/R/vuongtest.R b/R/vuongtest.R
index 57c5f6b..ae1985a 100644
--- a/R/vuongtest.R
+++ b/R/vuongtest.R
@@ -231,7 +231,7 @@ calcAB <- function(object, n, scfun, vc){
     ## in case mirt vcov was not estimated
     if(nrow(tmpvc) == 1 & is.na(tmpvc[1,1])) stop("Please re-estimate the mirt model with SE=TRUE")
   }
-  A <- chol2inv(chol(tmpvc))
+  Ainv <- tmpvc
 
   ## Eq (2.2)
   if(!is.null(scfun)){
@@ -251,9 +251,9 @@ calcAB <- function(object, n, scfun, vc){
     sc <- estfun(object)
   }
   sc.cp <- crossprod(sc)/n
-  B <- matrix(sc.cp, nrow(A), nrow(A))
+  B <- matrix(sc.cp, nrow(Ainv), nrow(Ainv))
 
-  list(A=A, B=B, sc=sc)
+  list(Ainv=Ainv, B=B, sc=sc)
 }
 
 ## a function to get the cross-product from Eq (2.7)
@@ -271,10 +271,10 @@ 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))))
+  W <- cbind(rbind(-AB1$B %*% AB1$Ainv,
+                   t(Bc) %*% AB1$Ainv),
+             rbind(-Bc %*% AB2$Ainv,
+                   AB2$B %*% AB2$Ainv))
 
   lamstar <- eigen(W, only.values=TRUE)$values
   ## Discard imaginary part, as it only occurs for tiny eigenvalues?