Abstract
Higher-order approximations to the distribution of the likelihood ratio statistic are considered for a class of nonregular models in which the maximum likelihood estimator of the parameter of interest is asymptotically distributed according to an exponential, rather than a normal, distribution. Asymptotic behaviour of this type often arises when the boundary of the support of the distributions under consideration depends on 9. A modified likelihood ratio statistic is proposed that follows its asymptotic distribution to a high degree of approximation, and this statistic is illustrated on several examples.
Original language | English (US) |
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Pages (from-to) | 603-612 |
Number of pages | 10 |
Journal | Biometrika |
Volume | 91 |
Issue number | 3 |
DOIs | |
State | Published - 2004 |
Keywords
- Higher-order asymptotic theory
- Likelihood ratio approximation
- Maximum likelihood
- Unknown endpoint
ASJC Scopus subject areas
- Statistics and Probability
- Mathematics(all)
- Agricultural and Biological Sciences (miscellaneous)
- Agricultural and Biological Sciences(all)
- Statistics, Probability and Uncertainty
- Applied Mathematics