Asymptotics for the likelihood ratio test in a two-component normal mixture model

This paper characterizes the asymptotic properties of the likelihood ratio test (LRT) statistic for testing homogeneity in a two-component normal mean mixture model. We justify that the LRT statistic 2λn is asymptotically equivalent to the square of the supremum of the stochastic process studied in Bickel and Chernoff (Statistics and Probability: A Raghu Raj Bahadur Festschrift (1993) 83). In particular, we prove that 2λn diverges to +∞ at a rate of loglogn which confirms a conjecture of Hartigan (Proceedings of Berkeley Conference in Honor of Jerzy Neyman and Jack Kiefer (1985)). More specifically, under the null hypothesis we prove the following fact: limn→∞P{2λn−loglogn+log(2π2)⩽x}=exp(−e−x/2),x∈R.

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