In this article, we describe jackknife2, a new prefix command for jackknifing linear estimators. It takes full advantage of the available leave-one-out formula, thereby allowing for substantial reduction in computing time. Of special note is that jackknife2 allows the user to compute cross-validation and diagnostic measures that are currently not available after ivregress 2sls, xtreg, and xtivregress.

Belotti, F., Peracchi, F. (2020). Fast leave-one-out methods for inference, model selection, and diagnostic checking. THE STATA JOURNAL, 20(4), 785-804 [10.1177/1536867X20976312].

Fast leave-one-out methods for inference, model selection, and diagnostic checking

Belotti, Federico
Software
;
Peracchi, Franco
2020-12-01

Abstract

In this article, we describe jackknife2, a new prefix command for jackknifing linear estimators. It takes full advantage of the available leave-one-out formula, thereby allowing for substantial reduction in computing time. Of special note is that jackknife2 allows the user to compute cross-validation and diagnostic measures that are currently not available after ivregress 2sls, xtreg, and xtivregress.
dic-2020
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore SECS-P/05 - ECONOMETRIA
English
Con Impact Factor ISI
jackknife2, jackknife, heteroskedasticity-consistent standard errors, cross-validation, diagnostic checking, predictive residuals
Belotti, F., Peracchi, F. (2020). Fast leave-one-out methods for inference, model selection, and diagnostic checking. THE STATA JOURNAL, 20(4), 785-804 [10.1177/1536867X20976312].
Belotti, F; Peracchi, F
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/262038
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