Stein’s method of moments for truncated multivariate distributions

We use Stein characterisations to derive new moment-type estimators for the parameters of several truncated multivariate distributions in the i.i.d. case; we also derive the asymptotic properties of these estima-tors. Our examples include the truncated multivariate normal distribution and truncated products of independent univariate distributions. The estimators are explicit, and therefore provide an interesting alternative to the maximum likelihood estimator (MLE). The quality of these estimators is assessed through competitive simulation studies, in which we compare their behavior to the performance of the MLE and the score-matching approach.

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Publication Details

Journal
Electronic Journal of Statistics
Published
2025-01-01
DOI
https://doi.org/10.1214/25-ejs2373
Citations
2
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
5.26
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article

Stein’s method of moments for truncated multivariate distributions

Adrian G. Fischer, Robert E. Gaunt, Yvik Swan
2 citations
Electronic Journal of Statistics
Statistical Distribution Estimation and Applications
5.26
article

Stein’s method of moments for truncated multivariate distributions

Adrian G. Fischer, Robert E. Gaunt, Yvik Swan
article en
2 citations

Abstract

We use Stein characterisations to derive new moment-type estimators for the parameters of several truncated multivariate distributions in the i.i.d. case; we also derive the asymptotic properties of these estima-tors. Our examples include the truncated multivariate normal distribution and truncated products of independent univariate distributions. The estimators are explicit, and therefore provide an interesting alternative to the maximum likelihood estimator (MLE). The quality of these estimators is assessed through competitive simulation studies, in which we compare their behavior to the performance of the MLE and the score-matching approach.

Electronic Journal of StatisticsVol. 19(1)
Université Libre de Bruxelles (BE), University of Manchester (GB), University of Oxford (GB)
Openalex Percentile: Top 6%
Statistical Distribution Estimation and Applications
5.26
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