R version 4.6.0 beta (2026-04-12 r89874 ucrt) -- "Because it was There"
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Platform: x86_64-w64-mingw32/x64

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> 
> library("mvtnorm")
> 
> set.seed(29)
> 
> chk <- function(...) stopifnot(isTRUE(all.equal(..., check.attributes = FALSE, tol = 1e-4)))
> 
> ### N samples with N different covariance matrices
> 
> N <- 2
> J <- 8
> 
> prm <- runif(N * J * (J + 1) / 2) + 1
> m <- matrix(rnorm(N * J), nrow = J)
> Z <- matrix(rnorm(N * J), ncol = N)
> W <- matrix(runif((J - 1) * 100), nrow = J - 1)
> 
> thischeck <- expression({
+   lt <- ltMatrices(matrix(prm[1: (N * J * (J + c(-1, 1)[dg + 1L]) / 2)], ncol = N), 
+                    diag = dg)
+   lt <- ltMatrices(lt, diag = dg, byrow = br)
+   d <- Mult(lt, m)
+   Y <- solve(lt, Z) + m
+   obs <- Y[idx1,]
+   lower <- Y[idx2,] - 2
+   upper <- Y[idx2,] + 2
+   w <- W[seq_len(length(idx2) - 1),,drop = FALSE]
+ 
+   objmL <- mvnorm(mean = m, invchol = lt)
+   objmC <- mvnorm(mean = m, chol = solve(lt))
+ 
+   l3 <- logLik(objmL, obs = obs, lower = lower, upper = upper, 
+                logLik = FALSE, w = w)
+   l4 <- logLik(objmC, obs = obs, lower = lower, upper = upper,
+                logLik = FALSE, w = w)
+ 
+   chk(l3, l4)
+ 
+   objiL <- mvnorm(invcholmean = d, invchol = lt)
+   objiC <- mvnorm(invcholmean = d, chol = solve(lt))
+ 
+   l3d <- logLik(objiL, obs = obs, lower = lower, upper = upper,
+                 logLik = FALSE, w = w)
+   l4d <- logLik(objiC, obs = obs, lower = lower, upper = upper,
+                 logLik = FALSE, w = w)
+ 
+   chk(l3, l3d)
+   chk(l4, l4d)
+ 
+   ### check scores
+   if (require("numDeriv", quietly = TRUE)) {
+ 
+     f <- function(L) {
+       L <- ltMatrices(L, diag = dg, byrow = br)
+       obj <- mvnorm(mean = m, invchol = L)
+       logLik(obj, obs = obs, lower = lower, upper = upper, w = w)
+     }
+ 
+     s0 <- grad(f, unclass(lt))
+     s1 <- lLgrad(objmL, obs = obs, lower = lower, upper = upper, w = w)
+ 
+     chk(Lower_tri(ltMatrices(matrix(s0, ncol = N), diag = dg, byrow = br), diag = dg), 
+         Lower_tri(s1$scale, diag = dg))
+ 
+     f <- function(L) {
+       L <- ltMatrices(L, diag = dg, byrow = br)
+       obj <- mvnorm(invcholmean = d, invchol = L)
+       logLik(obj, obs = obs, lower = lower, upper = upper, w = w)
+     }
+ 
+     s0 <- grad(f, unclass(lt))
+     s1 <- lLgrad(objiL, obs = obs, lower = lower, upper = upper, w = w)
+ 
+     chk(Lower_tri(ltMatrices(matrix(s0, ncol = N), diag = dg, byrow = br), diag = dg), 
+         Lower_tri(s1$scale, diag = dg))
+ 
+     f <- function(L) {
+       L <- ltMatrices(L, diag = dg, byrow = br)
+       obj <- mvnorm(mean = m, chol = L)
+       logLik(obj, obs = obs, lower = lower, upper = upper, w = w)
+     }
+ 
+     s0 <- grad(f, unclass(solve(lt)))
+     s1 <- lLgrad(objmC, obs = obs, lower = lower, upper = upper, w = w)
+ 
+     chk(Lower_tri(ltMatrices(matrix(s0, ncol = N), diag = dg, byrow = br), diag = dg), 
+         Lower_tri(s1$scale, diag = dg))
+ 
+     f <- function(L) {
+       L <- ltMatrices(L, diag = dg, byrow = br)
+       obj <- mvnorm(invcholmean = d, chol = L)
+       logLik(obj, obs = obs, lower = lower, upper = upper, w = w)
+     }
+ 
+     s0 <- grad(f, unclass(solve(lt)))
+     s1 <- lLgrad(objiC, obs = obs, lower = lower, upper = upper, w = w)
+ 
+     chk(Lower_tri(ltMatrices(matrix(s0, ncol = N), diag = dg, byrow = br), diag = dg), 
+         Lower_tri(s1$scale, diag = dg))
+ 
+     f <- function(x)
+       logLik(objmL, obs = x, lower = lower, upper = upper, w = w)
+ 
+     s0 <- grad(f, obs)
+     s1 <- lLgrad(objmL, obs = obs, lower = lower, upper = upper, w = w)
+ 
+     chk(matrix(s0, ncol = N), s1$obs)
+ 
+     f <- function(x)
+       logLik(objiL, obs = x, lower = lower, upper = upper, w = w)
+ 
+     s0 <- grad(f, obs)
+     s1 <- lLgrad(objiL, obs = obs, lower = lower, upper = upper, w = w)
+ 
+     chk(matrix(s0, ncol = N), s1$obs)
+ 
+     f <- function(lwr)
+       logLik(objmL, obs = obs, lower = lwr, upper = upper, w = w)
+ 
+     s0 <- grad(f, lower)
+     s1 <- lLgrad(objmL, obs = obs, lower = lower, upper = upper, w = w)
+ 
+     chk(matrix(s0, ncol = N), s1$lower)
+ 
+     f <- function(lwr)
+       logLik(objiL, obs = obs, lower = lwr, upper = upper, w = w)
+ 
+     s0 <- grad(f, lower)
+     s1 <- lLgrad(objiL, obs = obs, lower = lower, upper = upper, w = w)
+ 
+     chk(matrix(s0, ncol = N), s1$lower)
+ 
+     f <- function(upr)
+       logLik(objmL, obs = obs, lower = lower, upper = upr, w = w)
+ 
+     s0 <- grad(f, upper)
+     s1 <- lLgrad(objmL, obs = obs, lower = lower, upper = upper, w = w)
+ 
+     chk(matrix(s0, ncol = N), s1$upper)
+ 
+     f <- function(upr)
+       logLik(objiL, obs = obs, lower = lower, upper = upr, w = w)
+ 
+     s0 <- grad(f, upper)
+     s1 <- lLgrad(objiL, obs = obs, lower = lower, upper = upper, w = w)
+ 
+     chk(matrix(s0, ncol = N), s1$upper)
+ 
+     f <- function(m) {
+       obj <- mvnorm(mean = m, invchol = lt)
+       logLik(obj, obs = obs, lower = lower, upper = upper, w = w)
+     }
+ 
+     s0 <- grad(f, m)
+     s1 <- lLgrad(objmL, obs = obs, lower = lower, upper = upper, w = w)
+ 
+     chk(matrix(s0, ncol = N), s1$mean)
+ 
+     f <- function(d) {
+       obj <- mvnorm(invcholmean = d, invchol = lt)
+       logLik(obj, obs = obs, lower = lower, upper = upper, w = w)
+     }
+ 
+     s0 <- grad(f, d)
+     s1 <- lLgrad(objiL, obs = obs, lower = lower, upper = upper, w = w)
+ 
+     chk(matrix(s0, ncol = N), s1$invcholmean)
+   }
+ })
> 
> 
> idx <- seq_len(J)
> idx1 <- idx[1:4]
> idx2 <- idx[-(1:4)]
> 
> dg <- TRUE
> br <- FALSE
> eval(thischeck)
> 
> dg <- FALSE
> br <- FALSE
> eval(thischeck)
> 
> dg <- FALSE
> br <- TRUE
> eval(thischeck)
> 
> dg <- FALSE
> br <- FALSE
> eval(thischeck)
> 
> idx1 <- idx[-(1:4)]
> idx2 <- idx[1:4]
> 
> 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 
 121.42    2.29  123.85