tsZIC.test {ConfZIC} | R Documentation |

## Test whether two ZIC values differ significantly based on minimum ZIC for time series data

### Description

Test whether two ZIC values differ significantly based on minimum ZIC for time series data.

### Usage

```
tsZIC.test(x,model1,model2,model_ZIC="AIC",alpha=0.05)
```

### Arguments

`x` |
time series data (maximum of 1000 data points). |

`model1` |
AR and MA coefficients of Model 1. |

`model2` |
AR and MA coefficients of Model 2. |

`model_ZIC` |
type of the information criterion, it can be "AIC", "BIC", or "AICc" (Default is the "AIC"). |

`alpha` |
significance level |

### Details

Consider the hypothesis: Under the null hypothesis that the two expected discrepancies are equal.

`H_0: ZIC_i=ZIC_j , H_1: ZIC_i\neq ZIC_j`

`Z_0=\frac{(\hat{ZIC_i}-\hat{ZIC_j})-0}{\sqrt{SD(ZIC_i,ZIC_j)}} \sim N(0,1)`

is calculated empirically.

### Value

p-value with significance status.

### References

Linhart, H. (1988). A test whether two AIC's differ significantly. South African Statistical Journal, 22(2), 153-161.

### Examples

```
library(ConfZIC)
data(Sunspots)
x=Sunspots
model1=try(arima(x,order=c(1,0,1),method="ML",include.mean=FALSE),silent = TRUE)
model2=try(arima(x,order=c(1,0,0),method="ML",include.mean=FALSE),silent = TRUE)
tsZIC.test(x,model1,model2,model_ZIC="AIC",alpha=0.05)
```

*ConfZIC*version 1.0.1 Index]