Conditional quantile functions of MixAR models

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

Author

Georgi N. Boshnakov

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")

See also

mix_pdf, mix_cdf;

mix_moment for examples