R Under development (unstable) (2024-09-01 r87083 ucrt) -- "Unsuffered Consequences"
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> 
> library("mvtnorm")
> 
> set.seed(29)
> 
> chk <- function(...) stopifnot(isTRUE(all.equal(..., check.attributes = FALSE)))
> 
> ### N samples with N different covariance matrices
> 
> thischeck <- expression({
+   N <- 10
+   J <- 5
+   lt <- ltMatrices(matrix(runif(N * J * (J + c(-1, 1)[dg + 1L]) / 2) + 1, ncol = N), 
+                    diag = dg)
+   lt <- ltMatrices(lt, diag = dg, byrow = br)
+   Z <- matrix(rnorm(N * J), ncol = N)
+   Y <- solve(lt, Z)
+   ll1 <- sum(dnorm(Mult(lt, Y), log = TRUE)) + sum(log(diagonals(lt)))
+ 
+   S <- as.array(Tcrossprod(solve(lt)))
+   ll2 <- sum(l2 <- sapply(1:N, function(i) mvtnorm:::dmvnorm(x = Y[,i], sigma = S[,,i], log = TRUE)))
+   chk(ll1, ll2)
+ 
+   l3 <- ldmvnorm(obs = Y, invchol = lt, logLik = FALSE)
+   l4 <- ldmvnorm(obs = Y, chol = solve(lt), logLik = FALSE)
+ 
+   chk(l2, l3)
+   chk(l2, l4)
+ 
+   ll1 <- sum(dnorm(Mult(lt[1,], Y), log = TRUE)) + N * sum(log(diagonals(lt[1,])))
+ 
+   S <- as.array(Tcrossprod(solve(lt)))
+   ll2 <- sum(l2 <- sapply(1:N, function(i) mvtnorm:::dmvnorm(x = Y[,i], sigma = S[,,1], log = TRUE)))
+   chk(ll1, ll2)
+ 
+   l3 <- ldmvnorm(obs = Y, invchol = lt[1,], logLik = FALSE)
+   l4 <- ldmvnorm(obs = Y, chol = solve(lt[1,]), logLik = FALSE)
+ 
+   chk(l2, l3)
+   chk(l2, l4)
+ 
+   ### check scores
+   if (require("numDeriv", quietly = TRUE)) {
+ 
+     f <- function(L) {
+       L <- ltMatrices(L, diag = dg, byrow = br)
+       ldmvnorm(obs = Y, invchol = L)
+     }
+ 
+     s0 <- grad(f, unclass(lt))
+     s1 <- sldmvnorm(obs = Y, invchol = lt)
+ 
+     chk(Lower_tri(ltMatrices(matrix(s0, ncol = N), diag = dg, byrow = br), diag = dg), 
+         Lower_tri(s1$invchol, diag = dg))
+ 
+     f <- function(L) {
+       L <- ltMatrices(L, diag = dg, byrow = br)
+       ldmvnorm(obs = Y, chol = L)
+     }
+ 
+     s0 <- grad(f, unclass(lt))
+     s1 <- sldmvnorm(obs = Y, chol = lt)
+ 
+     chk(Lower_tri(ltMatrices(matrix(s0, ncol = N), diag = dg, byrow = br), diag = dg), 
+         Lower_tri(s1$chol, diag = dg))
+ 
+     f <- function(x)
+       ldmvnorm(obs = x, invchol = lt)
+ 
+     s0 <- grad(f, Y)
+     s1 <- sldmvnorm(obs = Y, invchol = lt)
+ 
+     chk(matrix(s0, ncol = N), s1$obs)
+   }
+ })
> 
> dg <- TRUE
> br <- FALSE
> eval(thischeck)
> 
> dg <- FALSE
> br <- FALSE
> eval(thischeck)
> 
> dg <- FALSE
> br <- TRUE
> eval(thischeck)
> 
> dg <- FALSE
> br <- FALSE
> eval(thischeck)
> 
> 
> proc.time()
   user  system elapsed 
   2.90    0.18    3.03