mix_qf-methods: Conditional quantile functions of MixAR models

In GeoBosh/mixAR: Mixture Autoregressive Models

Conditional quantile functions of MixAR models

Description

Gives conditional quantile functions of mixture autoregressive models.

Usage

mix_qf(model, p, x, index, xcond)

Arguments

model	mixAR model.
p	vector of probabilities.
x	time series.
index	vector of positive integers.
xcond	the past values needed for the conditional distribution, a numeric vector of length at least the maximal AR order of the components.

Value

depending on the arguments, a function for computing quantiles or a numeric vector representing quantiles, see sections 'Details' and 'Methods

Methods

signature(model = "MixARGaussian", p = "missing", x = "missing", index = "missing", xcond = "numeric")

signature(model = "MixARGaussian", p = "numeric", x = "missing", index = "missing", xcond = "numeric")

signature(model = "MixARGaussian", p = "numeric", x = "numeric", index = "numeric", xcond = "missing")

Author(s)

Georgi N. Boshnakov

See Also

mix_pdf, mix_cdf;

mix_moment for examples

GeoBosh/mixAR documentation built on May 9, 2022, 7:36 a.m.