# CIARfit: Fitted Values of CIAR model In iAR: Irregularly Observed Autoregressive Models

 CIARfit R Documentation

## Fitted Values of CIAR model

### Description

Fit a CIAR model to an irregularly observed time series.

### Usage

```CIARfit(phiValues, y, t, standardized = TRUE, c = 1)
```

### Arguments

 `phiValues` An array with the parameters of the CIAR model. The elements of the array are, in order, the real and the imaginary part of the phi parameter of the CIAR model. `y` Array with the time series observations. `t` Array with the irregular observational times. `standardized` logical; if TRUE, the array y is standardized; if FALSE, y contains the raw time series `c` Nuisance parameter corresponding to the variance of the imaginary part.

### Value

A list with the following components:

• yhat Fitted values of the observable part of CIAR model.

• xhat Fitted values of both observable part and imaginary part of CIAR model.

• Lambda Lambda value estimated by the CIAR model at the last time point.

• Theta Theta array estimated by the CIAR model at the last time point.

• Sighat Covariance matrix estimated by the CIAR model at the last time point.

• Qt Covariance matrix of the state equation estimated by the CIAR model at the last time point.

### References

\insertRef

Elorrieta_2019iAR

`gentime`, `CIARsample`, `CIARphikalman`,`CIARkalman`

### Examples

```n=100
set.seed(6714)
st<-gentime(n)
x=CIARsample(n=n,phiR=0.9,phiI=0,st=st,c=1)
y=x\$y
y1=y/sd(y)
ciar=CIARkalman(y=y1,t=st)
ciar
yhat=CIARfit(phiValues=c(ciar\$phiR,ciar\$phiI),y=y1,t=st)
```

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