TSSS (version 1.3.4-5)

klinfo: Kullback-Leibler Information

Description

Compute Kullback-Leibler information.

Usage

klinfo(distg = 1, paramg = c(0, 1), distf = 1, paramf, xmax = 10)

Value

nint

number of function evaluation.

dx

delta.

KLI

Kullback-Leibler information, \(I(g;f)\).

gint

integration of \(g(y)\) over [-xmax, xmax].

Arguments

distg

function for the true density (1 or 2).

1 :	Gaussian (normal) distribution
	paramg(1): mean
	paramg(2): variance
2 :	Cauchy distribution
	paramg(1): \(\mu\) (location parameter)
	paramg(2): \(\tau^2\) (dispersion parameter)

paramg

parameter vector of true density.

distf

function for the model density (1 or 2).

1 :	Gaussian (normal) distribution
	paramf(1): mean
	paramf(2): variance
2 :	Cauchy distribution
	paramf(1): \(\mu\) (location parameter)
	paramf(2): \(\tau^2\) (dispersion parameter)

paramf

parameter vector of the model density.

xmax

upper limit of integration. lower limit xmin = -xmax.

References

Kitagawa, G. (2020) Introduction to Time Series Modeling with Applications in R. Chapman & Hall/CRC.

Examples

# g:Gauss, f:Gauss
klinfo(distg = 1, paramg = c(0, 1), distf = 1, paramf = c(0.1, 1.5), xmax = 8)

# g:Gauss, f:Cauchy
klinfo(distg = 1, paramg = c(0, 1), distf = 2, paramf = c(0, 1), xmax = 8)