Nothing
## Part of the sparseHessianFD package
## Copyright (C) 2013-2017 Michael Braun
context("complex step")
test_that("binary_example_complex", {
set.seed(1234)
data(binary)
binary <- binary
N <- length(binary$Y)
k <- NROW(binary$X)
nvars <- as.integer(N*k + k)
P <- rnorm(nvars) ## random starting values
Omega <- diag(k)
priors <- list(inv.Omega = solve(Omega),
inv.Sigma = rWishart(1,k+5,diag(k))[,,1])
make.funcs <- function(D, priors, order.row) {
res <- vector("list", length=3)
names(res) <- c("fn", "gr", "hessian")
res$fn <- function(pars) {
binary.f(pars, data=D, priors=priors, order.row=order.row)
}
res$gr <- function(pars) {
binary.grad(pars, data=D, priors=priors, order.row=order.row)
}
res$hessian <- function(pars) {
binary.hess(pars, data=D, priors=priors, order.row=order.row)
}
return(res)
}
f1 <- make.funcs(D=binary, priors=priors, order.row=FALSE) ## block-arrow
f2 <- make.funcs(D=binary, priors=priors, order.row=TRUE) ## off-diagonals
## True values for test
true.val1 <- f1$fn(P)
true.grad1 <- f1$gr(P)
true.hess1 <- drop0(f1$hessian(P))
true.val2 <- f2$fn(P)
true.grad2 <- f2$gr(P)
true.hess2 <- drop0(f2$hessian(P))
## Get hessian structure
pat1 <- Matrix.to.Coord(tril(true.hess1))
pat2 <- Matrix.to.Coord(tril(true.hess2))
obj1 <- sparseHessianFD(P, f1$fn, f1$gr, pat1$rows, pat1$cols, complex=TRUE)
obj2 <- sparseHessianFD(P, f2$fn, f2$gr, pat2$rows, pat2$cols, complex=TRUE)
test.val1 <- obj1$fn(P)
test.grad1 <- obj1$gr(P)
test.hess1 <- obj1$hessian(P)
test.val2 <- obj2$fn(P)
test.grad2 <- obj2$gr(P)
test.hess2 <- obj2$hessian(P)
expect_equal(test.val1, true.val1)
expect_equal(test.grad1, true.grad1)
expect_equal(test.hess1, true.hess1)
expect_equal(test.val2, true.val2)
expect_equal(test.grad2, true.grad2)
expect_equal(test.hess2, true.hess2)
})
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.