effectiveSize_TAR: Effective sample size for 'mtar' objects

In mtarm: Bayesian Estimation of Multivariate Threshold Autoregressive Models

Effective sample size for mtar objects

Description

This function computes the effective sample size, adjusted for autocorrelation, of Markov chain Monte Carlo (MCMC) output obtained from the Bayesian estimation of multivariate TAR models. It serves as a wrapper around effectiveSize(), applying this function to the posterior chains returned by mtar().

Usage

effectiveSize_TAR(x)

Arguments

x	An object of class mtar produced by mtar().

Value

A list with the effective sample sizes for each parameter of the mtar model.

See Also

effectiveSize

Examples

###### Example 1: Returns of the closing prices of three financial indexes
data(returns)
fit1 <- mtar(~ COLCAP + BOVESPA | SP500, data=returns, row.names=Date,
             subset={Date<="2015-12-07"}, dist="Student-t",
             ars=ars(nregim=3,p=c(1,1,2)), n.burnin=1000, n.sim=2000,
             n.thin=2)
effectiveSize_TAR(fit1)

###### Example 2: Rainfall and two river flows in Colombia
data(riverflows)
fit2 <- mtar(~ Bedon + LaPlata | Rainfall, data=riverflows, row.names=Date,
             subset={Date<="2009-02-13"}, dist="Laplace",
             ars=ars(nregim=3,p=5), n.burnin=1000, n.sim=2000, n.thin=2)
effectiveSize_TAR(fit2)

###### Example 3: Temperature, precipitation, and two river flows in Iceland
data(iceland.rf)
fit3 <- mtar(~ Jokulsa + Vatnsdalsa | Temperature | Precipitation,
             data=iceland.rf, subset={Date<="1974-11-06"}, row.names=Date,
             ars=ars(nregim=2,p=15,q=4,d=2), n.burnin=1000, n.sim=2000,
             n.thin=2, dist="Slash")
effectiveSize_TAR(fit3)

###### Example 4: U.S. stock returns
data(US.returns)
fit4 <- mtar(~ CCR | dVIX, data=US.returns, subset={Date<="2025-11-28"},
             row.names=Date, ars=ars(nregim=2,p=3,d=3), n.burnin=1000,
             n.sim=2000, n.thin=2, dist="Student-t")
effectiveSize_TAR(fit4)

mtarm documentation built on June 12, 2026, 5:07 p.m.