A Note on Likelihood Ratio Tests for Models with Latent Variables

Generalized Likelihood Ratio Tests for Additive Models

Likelihood-ratio tests for hidden Markov models.

We consider hidden Markov models as a versatile class of models for weakly dependent random phenomena. The topic of the present paper is likelihood-ratio testing for hidden Markov models, and we show that, under appropriate conditions, the standard asymptotic theory of likelihood-ratio tests is valid. Such tests are crucial in the specification of multivariate Gaussian hidden Markov models, whi...

On likelihood ratio tests

Likelihood ratio tests are intuitively appealing. Nevertheless, a number of examples are known in which they perform very poorly. The present paper discusses a large class of situations in which this is the case, and analyzes just how intuition misleads us; it also presents an alternative approach which in these situations is optimal. 1. The popularity of likelihood ratio tests Faced with a new...

Power computation for likelihood ratio tests for the transition parameters in latent Markov models

Latent Markov (LM) models are increasingly used in a wide range of research areas including psychological, sociological, educational, and medical sciences. Methods to perform power computations are lacking, however. Power computations can help 1) to make an informed decision on the sample size or the number of measurement occasions required to achieve a prespecified power level of a statistical...

Likelihood Ratio Tests for