Theoretical analysis of power in a two-component normal mixture model

In a likelihood-ratio test for a two-component Normal location mixture, the natural parametrisation degenerates to non-uniqueness under the null hypothesis. One consequence of this ambiguity is that the limiting distribution of the likelihood-ratio statistic is quite irregular, being of extreme-value type rather than chi-squared. Another irregular feature is that the likelihood-ratio statistic diverges to infinity, and so limit theory is nonstandard in this respect as well. These results, in a form applying directly to the likelihood-ratio statistic rather than to an approximating stochastic process, have recently been established by Liu and Shao (2004). While they address only properties under the null hypothesis, they hint that the power of the likelihood-ratio test may be less than in more conventional settings. In this paper we show that this is indeed the case. Using a system of local alternative hypotheses we quantify the extent to which power is reduced. We show that, in a large class of circumstances, the reduction in power can be appreciated in terms of inflation (by a log-log factor) of the displacement of the closest local alternative that can just be distinguished from the null hypothesis. However, in important respects the properties of power under local alternatives are significantly more complex than this, and exhibit two types of singularity. In particular, in two quite different respects, small changes in the local alternative, in the neighbourhood of a threshold, can dramatically alter power