Now showing items 1-5 of 5

  • Hjort, Nils Lid; Claeskens, Gerda (Research report / Forskningsrapport, 2004)
    This article is concerned with variable selection methods for the proportional hazards regression model. Including too many covariates causes extra variability and inflated confidence intervals for regression parameters, ...
  • Claeskens, Gerda; Hjort, Nils Lid (Research report / Forskningsrapport, 2011)
    A variety of model selection criteria have been developed, of general and specific types. Most of these aim at selecting a single model with good overall properties, e.g. formulated via average prediction quality or shortest ...
  • Hjort, Nils Lid; Claeskens, Gerda (Research report / Forskningsrapport, 2003)
    The traditional use of model selection methods in practice is to proceed as if the final selected model had been chosen in advance, without acknowledging the additional uncertainty introduced by model selection. This often ...
  • Claeskens, Gerda; Hjort, Nils Lid (Research report / Forskningsrapport, 2003)
    To test if a density <I>f</I> is equal to a specified <I>f</I><SUB>0</SUB>, one knows by the Neyman-Pearson lemma the form of the optimal test at a specified alternative <I>f</I><SUB>1</SUB>. Any nonparametric density ...
  • Hjort, Nils Lid; Claeskens, Gerda (Research report / Forskningsrapport, 2003)
    This Statistical Research Report contains the complete written discussion generated by the two papers “Frequentist Model Average Estimators”, by Hjort and Claeskens, and “The Focussed Information Criterion”, by Claeskens ...