BIAR.fit: Fitted Values of BIAR model

Description Usage Arguments Value See Also Examples

Description

Fit a BIAR model to a bivariate irregularly observed time series.

Usage

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BIAR.fit(x, y1, y2, t, yerr1, yerr2, zero.mean = "TRUE")

Arguments

x

An array with the parameters of the BIAR model. The elements of the array are, in order, the autocorrelation and the cross correlation parameter of the BIAR model.

y1

Array with the observations of the first time series of the BIAR process.

y2

Array with the observations of the second time series of the BIAR process.

t

Array with the irregular observational times.

yerr1

Array with the measurements error standard deviations of the first time series of the BIAR process.

yerr2

Array with the measurements error standard deviations of the second time series of the BIAR process.

zero.mean

logical; if true, the array y has zero mean; if false, y has a mean different from zero.

Value

A list with the following components:

See Also

gentime, BIAR.sample, BIAR.phi.kalman, BIAR.kalman

Examples

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n=80
set.seed(6714)
st<-gentime(n)
x=BIAR.sample(n=n,phi.R=0.9,phi.I=0.3,sT=st,rho=0.9)
y=x$y
y1=y/apply(y,1,sd)
yerr1=rep(0,n)
yerr2=rep(0,n)
biar=BIAR.kalman(y1=y1[1,],y2=y1[2,],t=st,delta1 = yerr1,delta2=yerr2)
biar
predbiar=BIAR.fit(x=c(biar$phiR,biar$phiI),y1=y1[1,],y2=y1[2,],t=st,yerr1
 = rep(0,length(y[1,])),yerr2=rep(0,length(y[1,])))
rho=predbiar$rho
print(rho)
yhat=predbiar$fitted

iAR documentation built on April 15, 2021, 5:06 p.m.

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