⚡ Bolt: Replace sapply with vapply for performance and safety

.jules/bolt.md

@@ -15,3 +15,6 @@
 ## 2024-05-15 - [R Performance: ifelse Overhead]
 **Learning:** In R, ifelse evaluates both true and false branches entirely before subsetting, which is very inefficient for vector operations.
 **Action:** Optimize this by preallocating with res <- Y * 0 to preserve attributes and using vectorized subsetting like if any cond res subset <- ...
+## 2024-05-14 - R Type Inference Overhead
+**Learning:** `sapply()` over lists in R incurs significant overhead because it must deduce and attempt to simplify the return type dynamically.
+**Action:** Always prefer `vapply()` with a predefined return type template (e.g., `numeric(1)`) over `sapply()` when operating on lists where the expected output length and type are known in advance. This improves both execution speed and type safety.

R/llcont.R

@@ -407,7 +407,7 @@ llcont.lavaan <- function(x, ...){
   if(tolower(lavInspect(x, "options")$missing) == "ml.x") stop("cannot handle lavaan models with missing='ml.x'. consider using missing='ml'.", call. = FALSE)
   mispatts <- lavInspect(x, "patterns")
   if(any(class(mispatts) == "list")){
-    npatts <- max(sapply(mispatts, nrow))
+    npatts <- max(vapply(mispatts, nrow, numeric(1)))
   } else {
     npatts <- nrow(mispatts)
   }