A mixture of a normal distribution with random mean and variance -- Examples of inconsistency of maximum likelihood estimates

Fuente: arXiv
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Autor principal: Ritov, Ya'acov
Formato: Preprint
Publicado: 2024
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author Ritov, Ya'acov
author_facet Ritov, Ya'acov
contents We consider the estimation of the mixing distribution of a normal distribution where both the shift and scale are unobserved random variables. We argue that in general, the model is not identifiable. We give an elegant non-constructive proof that the model is identifiable if the shift parameter is bounded by a known value. However, we argue that the generalized maximum likelihood estimator is inconsistent even if the shift parameter is bounded and the shift and scale parameters are independent. The mixing distribution, however, is identifiable if we have more than one observations per any realization of the latent shift and scale.
format Preprint
id arxiv_https___arxiv_org_abs_2408_09195
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A mixture of a normal distribution with random mean and variance -- Examples of inconsistency of maximum likelihood estimates
Ritov, Ya'acov
Statistics Theory
We consider the estimation of the mixing distribution of a normal distribution where both the shift and scale are unobserved random variables. We argue that in general, the model is not identifiable. We give an elegant non-constructive proof that the model is identifiable if the shift parameter is bounded by a known value. However, we argue that the generalized maximum likelihood estimator is inconsistent even if the shift parameter is bounded and the shift and scale parameters are independent. The mixing distribution, however, is identifiable if we have more than one observations per any realization of the latent shift and scale.
title A mixture of a normal distribution with random mean and variance -- Examples of inconsistency of maximum likelihood estimates
topic Statistics Theory
url https://arxiv.org/abs/2408.09195