sqar {mcsm} | R Documentation |
This function illustrates some of coda
's criterions on the noisy squared AR model,
using a Metro-polis-Has-tings algorithm based on a random walk. Depending on the value of the
boolean multies
, those criterions are either the geweke.diag
and
heidel.diag
diagnostics, along with a Kolmo-gorov-Smir-nov test of our own, or
plot(mcmc.list())
if several parallel chains are produced together.
sqar(T = 10^4, multies = FALSE, outsave = FALSE, npara = 5)
T |
Number of MCMC iterations |
multies |
Boolean variable determining whether or not parallel chains are simulated |
outsave |
Boolean variable determining whether or not the MCMC output is saved |
npara |
Number of parallel chains |
This function produces plots and, if outsave
is TRUE
, it produces a
list
with value the MMC sample(s).
Christian P. Robert and George Casella
Chapter 8 of EnteR Monte Carlo Statistical Methods
ousqar=sqar(outsave=TRUE)