## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
library(rvinecopulib)
set.seed(601)

## ----bicop-derivatives--------------------------------------------------------
u2 <- rbicop(250, "gaussian", 0, 0.6)
fit2 <- bicop(u2, family_set = "gaussian")

score2 <- scores(u2, fit2)
hessian2 <- hessian(u2, fit2)
dim(score2)
hessian2
colSums(score2)

## ----fit-vine-----------------------------------------------------------------
n <- 220
z <- rnorm(n)
x <- cbind(
  z + rnorm(n),
  0.7 * z + rnorm(n),
  -0.5 * z + rnorm(n)
)
u <- pseudo_obs(x)
fit <- vinecop(
  u,
  structure = dvine_structure(1:3),
  family_set = "gaussian"
)
get_all_parameters(fit)

## ----vine-scores--------------------------------------------------------------
score <- scores(u, fit)
hess <- hessian(u, fit)
dim(score)
dim(hess)
summary(fit)

## ----stepwise-full------------------------------------------------------------
stepwise_gradient <- colSums(scores(u, fit, step_wise = TRUE))
full_gradient <- colSums(scores(u, fit, step_wise = FALSE))
rbind(stepwise = stepwise_gradient, full = full_gradient)

## ----keep-all-----------------------------------------------------------------
full <- dvinecop(u[1:5, ], fit, keep_all = TRUE)
names(full)
full$pdf

## ----varying-bicop------------------------------------------------------------
points <- matrix(runif(200), ncol = 2)
rho <- seq(-0.8, 0.8, length.out = nrow(points))

density <- dbicop(points, "gaussian", 0, parameters = rho)
score_varying <- scores(points, bicop_dist("gaussian"), parameters = rho)
hessian_varying <- hessian(
  points,
  bicop_dist("gaussian"),
  parameters = rho
)
head(cbind(rho, density, score_varying))

## ----varying-vine-------------------------------------------------------------
base_parameters <- unlist(get_all_parameters(fit), use.names = FALSE)
parameter_matrix <- matrix(
  rep(base_parameters, each = nrow(u)),
  nrow = nrow(u)
)
parameter_matrix[, 1] <- seq(-0.6, 0.6, length.out = nrow(u))

density_varying <- dvinecop(u, fit, parameters = parameter_matrix)
score_varying <- scores(u, fit, parameters = parameter_matrix)
head(density_varying)
dim(score_varying)