Description Usage Arguments Value Author(s)
Functions to evaluate and sample from the PC prior for an AR(p) model
1 2 3 | inla.pc.ar.rpacf(n=1, p, lambda = 1)
inla.pc.ar.dpacf(pac, lambda = 1, log = TRUE)
|
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. |
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.
Havard Rue hrue@math.ntnu.no
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