Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1977 · 1.3K citations · 3 references
Parameter IdentificationDensity EstimationEngineeringMaximum Likelihood EstimationParameter EstimationPredictive AnalyticsSemi-nonparametric EstimationAsymptotic EquivalencePredictive ModelingManagementBiostatisticsStatistical InferenceModel ComparisonEstimation TheoryPredicting DensityStatisticsPrediction Modelling
Summary A logarithmic assessment of the performance of a predicting density is found to lead to asymptotic equivalence of choice of model by cross-validation and Akaike's criterion, when maximum likelihood estimation is used within each model.
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