Functions to evaluate and sample from the PC prior for an AR(p) model

inla.pc.ar.rpacf(n=1, p, lambda = 1)
    inla.pc.ar.dpacf(pac, lambda = 1, log = TRUE)

Arguments

p

The order of the AR-model

pac

A vector of partial autocorrelation coefficients

n

Number of observations

lambda

The rate parameter in the prior

log

Logical. Return the density in natural or log-scale.

Details

Value

inla.pc.ar.rpac generate samples from the prior, returning a matrix where each row is a sample of theta. inla.pc.ar.dpac evaluates the density of pac. Use inla.ar.pacf2phi, inla.ar.phi2pacf, inla.ar.pacf2acf and inla.ar.acf2pacf to convert between various parameterisations.

Author

Havard Rue hrue@r-inla.org

Examples