sim_functions: Sampling Functions for Innovations

In fEGarch: SM/LM EGARCH & GARCH, VaR/ES Backtesting & Dual LM Extensions

Sampling Functions for Innovations

Description

Draw random samples from a normal distribution, t-distribution, generalized error distribution, or their skewed variants (all standardized to have mean zero and variance one).

Usage

rnorm_s(n)

rstd_s(n, df = 10000)

rged_s(n, shape = 2)

rsged_s(n, shape = 2, skew = 1)

rald_s(n, P = 8)

rsnorm_s(n, skew = 1)

rsstd_s(n, df = 10000, skew = 1)

rsald_s(n, P = 8, skew = 1)

Arguments

n	the number of observations to draw.
df	the degrees of freedom for a (skewed) t-distribution.
shape	the shape parameter for a (skewed) generalized error distribution.
skew	the skewness parameter in the skewed distributions.
P	the number of Laplace distributions (minus 1) to derive the arithmetic mean from as the basis for a (skewed) average Laplace (AL) distribution distribution.

Details

Draw random samples from a normal distribution, t-distribution, generalized error distribution, an average Laplace distribution, or their skewed variants (all standardized to have mean zero and variance one).

Value

These functions return a numeric vector of length n.

Examples

rnorm_s(10)

rsstd_s(10, df = 7, skew = 0.9)

fEGarch documentation built on Sept. 11, 2025, 5:11 p.m.