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Type 'q()' to quit R. > > 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 16.92 0.59 17.50