svine_pseudo_residuals: Pseudo-residuals of S-vine models

In svines: Stationary Vine Copula Models

Pseudo-residuals of S-vine models

Description

Pseudo-residuals are defined as the Rosenblatt transform of the data, conditional on the past. Under a correctly specified model, they are approximately iid uniform on [0, 1]^d.

Usage

svine_pseudo_residuals(x, model, cores = 1)

Arguments

x	the data.
model	model inheriting from class svine_dist.
cores	number of cores to use; if larger than one, computations are performed in parallel on cores batches.

Value

An n-by-d matrix of pseudo-residuals, where n = NROW(x) - model$copula$p and d is the cross-sectional dimension.

Examples

# load data set
data(returns)  

dat <- returns[1:100, 1:3]

# fit parametric S-vine model with Markov order 1
fit <- svine(dat, p = 1, family_set = "parametric")

# compute pseudo-residuals
# (should be independent uniform across variables and time)
v <- svine_pseudo_residuals(dat, fit)
pairs(cbind(v[-1, ], v[-nrow(v), ]))

svines documentation built on Sept. 1, 2026, 1:08 a.m.