r.cond.ar2: Generate Random AR(2) Time Series

In CepLDA: Discriminant Analysis of Time Series in the Presence of Within-Group Spectral Variability

Description

Simulates multiple AR(2) time series.

Usage

r.cond.ar2(N,nj,r.phi1,r.phi2,r.sig2)

Arguments

N	Length of the series
nj	Number of series generated.
r.phi1	Range of first AR order coefficient. It is a vector contains minimum and maximum possible coefficients.
r.phi2	Range of second AR order coefficient. It is a vector contains minimum and maximum possible coefficients.
r.sig2	Range of conditional innovation variances. It is a vector contains minimum and maximum possible variances.

Value

a list with 2 elements

X	N by nj matrix of time series
cep	3 by nj matrix of parameters (phi1, phi2, sig2)

Author(s)

Robert Krafty <[e-mail]>

References

Krafty, RT (2016) Discriminant Analysis of Time Series in the Presence of Within-Group Spectral Variability. Journal of Time series analysis

See Also

cep.lda

Examples

## Simulate data
nj = 50  #number of series in training data
N = 500  #length of time series
data1 <- r.cond.ar2(N=N,nj=nj,r.phi1=c(.01,.7),r.phi2=c(-.12,-.06),r.sig2=c(.3,3))
data2 <- r.cond.ar2(N=N,nj=nj,r.phi1=c(.5,1.2),r.phi2=c(-.36,-.25),r.sig2=c(.3,3))
data3 <- r.cond.ar2(N=N,nj=nj,r.phi1=c(.9,1.5),r.phi2=c(-.56,-.75),r.sig2=c(.3,3))
data <- cbind(data1$X,data2$X,data3$X)
y <- c(rep(1,nj),rep(2,nj),rep(3,nj))  

CepLDA documentation built on May 1, 2019, 6:50 p.m.