find_dist: Optimal Distribution Fitting to IID Data

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

Optimal Distribution Fitting to IID Data

Description

Given a series supposed to be from independent and identically distributed (iid) random variables, fit all eight distributions of this package to the data using maximum-likelihood estimation (MLE) and select the best one following either the BIC (the default) or the AIC.

Usage

find_dist(
  x,
  dists = c("norm", "std", "ged", "ald", "snorm", "sstd", "sged", "sald"),
  fix_mean = NULL,
  fix_sdev = NULL,
  Prange = c(1, 5),
  criterion = c("bic", "aic")
)

Arguments

x	the vector of iid values to fit distributions to.
dists	a vector with all the distribution abbreviations which should be considered in the selection process; by default, all eight distributions of this package are considered.
fix_mean	a value to fix the unconditional mean of the distribution to; with the default NULL, the unconditional mean is estimated as an extra parameter.
fix_sdev	a value to fix the unconditional standard deviation of the distribution to; with the default NULL, the unconditional standard deviation is estimated as an extra parameter.
Prange	a two-element vector giving the search range for the shape parameter P of the (skewed) average Laplace distribution.
criterion	either "bic" or "aic" to use BIC or AIC as the final selection criterion; by default "bic" is implemented.

Details

For information on the method and distributions, we refer the reader to distr_est.

Value

Returns an object of class "fEGarch_distr_est" with various slots representing the estimation results of the selected fitted distribution.

Examples

x <- rnorm(2000) * 2.1 + 10.5
find_dist(x)

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