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 \alpha for the hypothesis testing (Default is 0.05).

### 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)


[Package ConfZIC version 1.0.1 Index]