id: 01088791
dt: j
an: 01088791
au: Konishi, Sadanori; Kitagawa, Genshiro
ti: Generalized information criteria in model selection.
so: Biometrika 83, No.4, 875-890 (1996).
py: 1996
pu: Biometrika Trust, Department of Statistical Science, University College
    London; Oxford University Press, Oxford
la: EN
cc: 
ut: information criteria; Bayes approach; efficient bootstrap simulation;
    $M$-estimators; AIC; predictive distribution; statistical functional;
    robust estimation; penalised likelihood
ci: 
li: doi:10.1093/biomet/83.4.875
    http://www3.oup.co.uk/biomet/hdb/Volume_83/Issue_04/
ab: Summary: The problem of evaluating the goodness of statistical models is
    investigated from an information-theoretic point of view. Information
    criteria are proposed for evaluating models constructed by various
    estimation procedures when the specified family of probability
    distributions does not contain the distribution generating the data.
    The proposed criteria are applied to the evaluation of models estimated
    by maximum likelihood, robust, penalised likelihood, Bayes procedures,
    etc. We also discuss the use of the bootstrap in model evaluation
    problems and present a variance reduction technique in the bootstrap
    simulation.
rv: