# BIARsample: Simulate from a BIAR Model In iAR: Irregularly Observed Autoregressive Models

 BIARsample R Documentation

## Simulate from a BIAR Model

### Description

Simulates a BIAR Time Series Model

### Usage

```BIARsample(n, st, phiR, phiI, delta1 = 0, delta2 = 0, rho = 0)
```

### Arguments

 `n` Length of the output bivariate time series. A strictly positive integer. `st` Array with observational times. `phiR` Autocorrelation coefficient of BIAR model. A value between -1 and 1. `phiI` Crosscorrelation coefficient of BIAR model. A value between -1 and 1. `delta1` Array with the measurements error standard deviations of the first time series of the bivariate process. `delta2` Array with the measurements error standard deviations of the second time series of the bivariate process. `rho` Contemporary correlation coefficient of BIAR model. A value between -1 and 1.

### Details

The chosen phiR and phiI values must satisfy the condition \$|phiR + i phiI| < 1\$.

### Value

A list with the following components:

• y Matrix with the simulated BIAR process.

• t Array with observation times.

• Sigma Covariance matrix of the process.

### References

\insertRef

Elorrieta_2021iAR

`gentime`

### Examples

```n=300
set.seed(6714)
st<-gentime(n)
x=BIARsample(n=n,phiR=0.9,phiI=0.3,st=st)
plot(st,x\$y[1,],type='l')
plot(st,x\$y[2,],type='l')
x=BIARsample(n=n,phiR=-0.9,phiI=-0.3,st=st)
plot(st,x\$y[1,],type='l')
plot(st,x\$y[2,],type='l')
```

iAR documentation built on Nov. 25, 2022, 1:06 a.m.