Generalized likelihood ratio and regular asymptotics
For nested parametric models, Λ is the null-model supremum likelihood divided by the full-model supremum likelihood.
Key knowledge
For nested parametric models, Λ is the null-model supremum likelihood divided by the full-model supremum likelihood. Reject for large −2 log Λ; for regular iid models and an interior smooth null submodel it converges under the null to χ² with degrees of freedom equal to the model-dimension difference.
Conditions and scope
- Identifiability, consistent asymptotically normal fitting, nonsingular information and differentiability regularity are required.
- Boundary parameters, singularities and small samples can invalidate this chi-square calibration.
Sources · 1
References
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Evidence and review
Definitions and Theorems 22.2–22.3; interior means relative to the respective smooth parameterizations.
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