Automatic selection of indicators in a fully saturated regression
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Automatic selection of indicators in a fully saturated regression. / Hendry, David F.; Johansen, Søren; Santos, Carlos.
I: Computational Statistics, Bind 23, Nr. 2, 2008, s. 317-335.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Automatic selection of indicators in a fully saturated regression
AU - Hendry, David F.
AU - Johansen, Søren
AU - Santos, Carlos
PY - 2008
Y1 - 2008
N2 - We consider selecting a regression model, using a variant of Gets, when there are more variables than observations, in the special case that the variables are impulse dummies (indicators) for every observation. We show that the setting is unproblematic if tackled appropriately, and obtain the finite-sample distribution of estimators of the mean and variance in a simple location-scale model under the null that no impulses matter. A Monte Carlo simulation confirms the null distribution, and shows power against an alternative of interest.
AB - We consider selecting a regression model, using a variant of Gets, when there are more variables than observations, in the special case that the variables are impulse dummies (indicators) for every observation. We show that the setting is unproblematic if tackled appropriately, and obtain the finite-sample distribution of estimators of the mean and variance in a simple location-scale model under the null that no impulses matter. A Monte Carlo simulation confirms the null distribution, and shows power against an alternative of interest.
KW - Faculty of Social Sciences
KW - regression saturation
KW - subset selection
KW - Model selection
U2 - 10.1007/s00180-007-0054-z
DO - 10.1007/s00180-007-0054-z
M3 - Journal article
VL - 23
SP - 317
EP - 335
JO - Computational Statistics
JF - Computational Statistics
SN - 0943-4062
IS - 2
ER -
ID: 9173250