R version 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup"
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Platform: x86_64-w64-mingw32/x64

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> 
> library("tram")
Loading required package: mlt
Loading required package: basefun
Loading required package: variables
Loading required package: mvtnorm
> set.seed(29)
> 
> chk <- function(...) 
+     stopifnot(isTRUE(all.equal(..., tol = 1e-6, check.attributes = FALSE)))
> 
> thischeck <- expression({
+   ltM <- function(x) ltMatrices(x, diag = FALSE, byrow = TRUE)
+   ltD <- function(x) ltMatrices(x, diag = TRUE, byrow = TRUE)
+   prm <- matrix(runif(J * (J - 1) / 2 * N), ncol = N)
+   L <- ltM(prm)
+ 
+   obs <- matrix(rnorm(J * N), ncol = N)
+   lwr <- -2 -abs(obs)
+   upr <- 2 + abs(obs)
+ 
+   fun <- tram:::.ll(c(J, 0), standardize = FALSE)
+   sum(fun$logLik(obs, L))
+   s <- fun$score(obs, L)
+ 
+   f <- function(obs = obs, L = L) 
+     sum(fun$logLik(obs, ltM(L)))
+   S <- matrix(grad(f, unclass(L), obs = obs), ncol = N)
+   chk(S, Lower_tri(s$Lambda))
+   S <- matrix(grad(f, obs, L = L), ncol = N)
+   chk(S, s$obs)
+ 
+   fun <- tram:::.ll(c(J, 0), standardize = TRUE)
+   sum(fun$logLik(obs, L))
+ 
+   LD <- invcholD(L)
+   sum(-colSums(Mult(LD, obs)^2 - log(diagonals(LD)^2)))
+ 
+   C <- solve(L)
+   CCt <- Tcrossprod(C, diag_only = TRUE)
+   LD <- invcholD(L, D = sqrt(CCt))
+   sum(-colSums(Mult(LD, obs)^2 - log(CCt)))
+ 
+   f <- function(obs, a) {
+     LD <- ltMatrices(a, diag = TRUE, byrow = TRUE)
+     sum(-colSums(Mult(LD, obs)^2 - log(diagonals(LD)^2)))
+   }
+   f(obs = obs, LD)
+ 
+   sLD <- ltMatrices(matrix(grad(f, unclass(LD), obs = obs), ncol = N), 
+                     diag = TRUE, byrow = TRUE)
+   sobs <- matrix(grad(f, obs, a = unclass(LD)), ncol = N)
+ 
+   sLDfun <- function(obs, LD) {
+     cJ <- dim(LD)[2L]
+     Y <- matrix(obs, byrow = TRUE, nrow = cJ, ncol = N * cJ)
+     tmp <- -2 * Mult(LD, Mult(LD, obs), transpose = TRUE)
+     ret <- - 2 * matrix(Mult(LD, obs)[, rep(1:N, each = cJ)] * Y, ncol = N)
+     M <- matrix(1:(cJ^2), nrow = cJ, byrow = FALSE)
+     ret <- ltMatrices(ret[M[lower.tri(M, diag = TRUE)],,drop = FALSE], 
+                           diag = TRUE, byrow = FALSE)
+     ret <- ltMatrices(ret, 
+                       diag = TRUE, byrow = TRUE)
+     diagonals(ret) <- diagonals(ret) + 2 / diagonals(LD)
+     return(list(Lambda = ret, obs = tmp))
+   }
+ 
+   s <- sLDfun(obs, LD)
+   chk(s$Lambda, sLD)
+   chk(s$obs, sobs)
+ 
+   s <- fun$score(obs, L)
+ 
+   f <- function(obs = obs, L = L) 
+     sum(fun$logLik(obs, ltM(L)))
+   S <- matrix(grad(f, unclass(L), obs = obs), ncol = N)
+   chk(S, Lower_tri(s$Lambda))
+   S <- matrix(grad(f, obs, L = L), ncol = N)
+   chk(S, s$obs)
+ 
+   w <- matrix(runif((J - 1) * M), ncol = M)
+   fun <- tram:::.ll(c(0, J), standardize = FALSE, list(w = w))
+   sum(fun$logLik(lower = lwr, upper = upr, Lambda = L))
+   s <- fun$score(lower = lwr, upper = upr, Lambda = L)
+ 
+   f <- function(lwr = lwr, upr = upr, L = L) 
+     sum(fun$logLik(lower = lwr, upper = upr, Lambda = ltM(L)))
+   S <- grad(f, unclass(L), lwr = lwr, upr = upr)
+   chk(S, c(Lower_tri(s$Lambda)))
+ 
+   S <- matrix(grad(f, lwr, upr = upr, L = L), ncol = N)
+   chk(S, s$lower)
+   S <- matrix(grad(f, upr, lwr = lwr, L = L), ncol = N)
+   chk(S, s$upper)
+ 
+   fun <- tram:::.ll(c(0, J), standardize = TRUE, list(w = w))
+   sum(fun$logLik(lower = lwr, upper = upr, Lambda = L))
+   s <- fun$score(lower = lwr, upper = upr, Lambda = L)
+ 
+   f <- function(lwr = lwr, upr = upr, L = L) 
+     sum(fun$logLik(lower = lwr, upper = upr, Lambda = ltM(L)))
+   S <- matrix(grad(f, unclass(L), lwr = lwr, upr = upr), ncol = N)
+   chk(S, Lower_tri(s$Lambda))
+   S <- matrix(grad(f, lwr, upr = upr, L = L), ncol = N)
+   chk(S, s$lower)
+   S <- matrix(grad(f, upr, lwr = lwr, L = L), ncol = N)
+   chk(S, s$upper)
+ 
+   w <- matrix(runif((dJ - 1) * M), ncol = M)
+   fun <- tram:::.ll(c(cJ, dJ), standardize = FALSE, list(w = w))
+   sum(fun$logLik(obs[1:cJ,,drop = FALSE], lwr[-(1:cJ),,drop = FALSE], upr[-(1:cJ),,drop = FALSE], L))
+   s <- fun$score(obs[1:cJ,,drop = FALSE], lwr[-(1:cJ),,drop = FALSE], upr[-(1:cJ),,drop = FALSE], L)
+   f <- function(obs = obs[1:cJ,,drop = FALSE], lwr = lwr[-(1:cJ),,drop = FALSE], upr = upr[-(1:cJ),,drop = FALSE], L = L) 
+     sum(fun$logLik(obs, lwr, upr, ltM(L)))
+   S <- matrix(grad(f, unclass(L), obs = obs[1:cJ,,drop = FALSE], lwr = lwr[-(1:cJ),,drop = FALSE], 
+                  upr = upr[-(1:cJ),,drop = FALSE]), ncol = N)
+   chk(S, Lower_tri(s$Lambda))
+   S <- matrix(grad(f, obs[1:cJ,,drop = FALSE], lwr = lwr[-(1:cJ),,drop = FALSE], 
+                     upr = upr[-(1:cJ),,drop = FALSE], L = L), ncol = N)
+   chk(S, s$obs)
+   S <- matrix(grad(f, lwr[-(1:cJ),,drop = FALSE], obs = obs[1:cJ,,drop = FALSE], 
+                     upr = upr[-(1:cJ),,drop = FALSE], L = L), ncol = N)
+   chk(S, s$lower)
+   S <- matrix(grad(f, upr[-(1:cJ),,drop = FALSE], obs = obs[1:cJ,,drop = FALSE], 
+                     lwr = lwr[-(1:cJ),,drop = FALSE], L = L), ncol = N)
+   chk(S, s$upper)
+ 
+   fun <- tram:::.ll(c(cJ, dJ), standardize = TRUE, list(w = w))
+   sum(fun$logLik(obs[1:cJ,,drop = FALSE], lwr[-(1:cJ),,drop = FALSE], upr[-(1:cJ),,drop = FALSE], L))
+   s <- fun$score(obs[1:cJ,,drop = FALSE], lwr[-(1:cJ),,drop = FALSE], 
+                  upr[-(1:cJ),,drop = FALSE], L)
+ 
+   f <- function(obs = obs[1:cJ,,drop = FALSE], lwr = lwr[-(1:cJ),,drop = FALSE], upr = upr[-(1:cJ),,drop = FALSE], L = L) 
+     sum(fun$logLik(obs, lwr, upr, ltM(L)))
+   S <- matrix(grad(f, unclass(L), obs = obs[1:cJ,,drop = FALSE], lwr = lwr[-(1:cJ),,drop = FALSE], 
+                  upr = upr[-(1:cJ),,drop = FALSE]), ncol = N)
+   chk(S, Lower_tri(s$Lambda))
+ 
+   S <- matrix(grad(f, obs[1:cJ,,drop = FALSE], lwr = lwr[-(1:cJ),,drop = FALSE], 
+                     upr = upr[-(1:cJ),,drop = FALSE], L = L), ncol = N)
+   chk(S, s$obs)
+   S <- matrix(grad(f, lwr[-(1:cJ),,drop = FALSE], obs = obs[1:cJ,,drop = FALSE], 
+                     upr = upr[-(1:cJ),,drop = FALSE], L = L), ncol = N)
+   chk(S, s$lower)
+   S <- matrix(grad(f, upr[-(1:cJ),,drop = FALSE], obs = obs[1:cJ,,drop = FALSE], 
+                     lwr = lwr[-(1:cJ),,drop = FALSE], L = L), ncol = N)
+   chk(S, s$upper)
+ 
+ })
> 
> 
> if (require("numDeriv", quietly = TRUE)) {
+ 
+ J <- (cJ <- 5) + (dJ <- 6)
+ N <- 3
+ M <- 10
+ 
+ eval(thischeck)
+ 
+ J <- (cJ <- 1) + (dJ <- 1)
+ 
+ eval(thischeck)
+ 
+ J <- (cJ <- 1) + (dJ <- 4)
+ 
+ eval(thischeck)
+ 
+ J <- (cJ <- 4) + (dJ <- 1)
+ 
+ eval(thischeck)
+ 
+ }
> 
> proc.time()
   user  system elapsed 
  18.31    0.87   19.17