Variance of the Impulse Indicator Saturation Gauge

Computes the variance of the gauge (false-positive rate of outliers under the null of no outliers) in impulse indicator saturation based on Jiao and Pretis (2019).

Usage

vargaugeiis(t.pval, T, infty=FALSE, m=1)

Arguments

t.pval: numeric, between 0 and 1. Selection p-value used in indicator saturation.
T: integer, sample sized used in indicator saturation.
m: integer, number of iterations in variance computation, default=1
infty: logical, argument used for variance computation

Details

The function computes the variance of the Gauge (false-positive rate of outliers in impulse indicator saturation) for a given level of significance of selection (t.pval) and sample size (T) based on Jiao and Pretis (2019). This is an auxilliary function used within the outliertest function.

Value

Returns a dataframe of the variance and standard deviation of the gauge, as well the asymptotic variance and standard deviation.

References

Jiao, X. & Pretis, F. (2019). Testing the Presence of Outliers in Regression Models. Discussion Paper.

Pretis, F., Reade, J., & Sucarrat, G. (2018). Automated General-to-Specific (GETS) regression modeling and indicator saturation methods for the detection of outliers and structural breaks. Journal of Statistical Software, 86(3).

Author

Felix Pretis, http://www.felixpretis.org/

Examples

  ###Computing the variance of the gauge under the null for a sample of T=200 observations:
  vargaugeiis(t.pval=0.05, T=200, infty=FALSE, m=1)
#>   var_iisgauge sd_iisgauge asy_var_iisgauge asy_sd_iisgauge
#> 1 0.0001062824  0.01030934       0.02125649       0.1457961