View source: R/gets-isat-source.R
isatvarcorrect | R Documentation |
Takes an isat
object and corrects the estimates of the error variance and the estimated standard errors of 'forced' regressors.
isatvarcorrect(x, mcor=1)
x |
an |
mcor |
integer, number of iterations in the correction. Default = 1. |
Impulse indicator saturation results in an under-estimation of the error variance as well as the variance of regressors not selected over. The magnitude of the inconsistency increases with the p-value of selection (t.pval
). The function takes an isat
object and applies the impulse indicator consistency (isvarcor
) and efficiency correction (isvareffcor
) of the estimated error variance and the estimated variance of regressors not selected over. See Johansen and Nielsen (2016a) and (2016b).
Returns an isat
object in which the estimated standard errors, t-statistics, p-values, standard error of the regression, and log-likelihood are consistency and efficiency corrected when using impulse indicator saturation (iis=TRUE
).
Felix Pretis, https://felixpretis.climateeconometrics.org/
Johansen, S., & Nielsen, B. (2016a). Asymptotic theory of outlier detection algorithms for linear time series regression models. Scandinavian Journal of Statistics, 43(2), 321-348.
Johansen, S., & Nielsen, B. (2016b). Rejoinder: Asymptotic Theory of Outlier Detection Algorithms for Linear. Scandinavian Journal of Statistics, 43(2), 374-381.
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).
isat
, isvarcor
, isvareffcor
###Consistency and Efficiency Correction of Impulse Indicator Estimates
nile <- as.zoo(Nile)
isat.nile <- isat(nile, sis=FALSE, iis=TRUE, plot=TRUE, t.pval=0.1)
isat.nile.corrected <- isatvarcorrect(isat.nile)
isat.nile$sigma2
isat.nile.corrected$sigma2
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