ARIMA.BIC {changepointGA} | R Documentation |
Example function: Calculating BIC for AR(1) model
Description
The objective function for changepoint search in Autoregressive moving average with model order selection via Bayesian Information Criterion (BIC).
Usage
ARIMA.BIC(chromosome, plen = 0, XMat, Xt)
Arguments
chromosome |
The chromosome consists of the number of changepoints, the order of AR part, the order of MA part, the changepoint locations, and a value of time series length plus 1 (N+1) indicating the end of the chromosome. |
plen |
The number of model order parameters that need to be selected.
If model order selection needs to be performed simultaneously with the
changepoint detection task, |
XMat |
A matrix contains the covariates, but not includes changepoint effects, for time series regression. |
Xt |
The simulated ARMA time series from |
Value
The BIC value of the objective function.
Examples
Ts = 1000
betaT = c(0.5) # intercept
XMatT = matrix(1, nrow=Ts, ncol=1)
colnames(XMatT) = "intercept"
sigmaT = 1
phiT = c(0.5)
thetaT = NULL
DeltaT = c(2, -2)
Cp.prop = c(1/4, 3/4)
CpLocT = floor(Ts*Cp.prop)
myts = ts.sim(beta=betaT, XMat=XMatT, sigma=sigmaT, phi=phiT, theta=thetaT,
Delta=DeltaT, CpLoc=CpLocT, seed=1234)
# candidate changepoint configuration
chromosome = c(2, 250, 750, 1001)
ARIMA.BIC(chromosome, XMat=XMatT, Xt=myts)
[Package changepointGA version 0.1.1 Index]