Automatic selection of indicators in a fully saturated regression

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

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.

TidsskriftComputational Statistics
Udgave nummer2
Sider (fra-til)317-335
Antal sider19
StatusUdgivet - 2008

ID: 9173250