Confidence intervals for discrete log-linear models when MLE does not exist

Nanwei Wang, Hélène Massam and Qiong Li

Statistics & Probability Letters, 2022, vol. 187, issue C

Abstract: The aim of this paper is to provide a methodology and MATLAB programs to compute confidence intervals for the cell probability parameters in a high-dimensional discrete log-linear model when the maximum likelihood estimate of these parameters does not exist. To do so, we use the geometry of exponential families as well as recent methodology to identify the submodel for which the maximum likelihood estimate exists. We illustrate our results with both simulated and real world data.

Keywords: Existence of the maximum likelihood estimate; Geometry of the exponential family of distributions; Confidence intervals; Directions of constancy; Directions of recession (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1016/j.spl.2022.109532

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