Loss of information in the presence of nuisance parameters and partial sufficiency
type: Item
instance of: scholarly article
title: Loss of information in the presence of nuisance parameters and partial sufficiency
zbMATH Open document ID: 0734.62008
DOI: 10.1016/0378-3758(91)90025-A
author: Vasant P. Bhapkar
published in: Journal of Statistical Planning and Inference
publication date: 1991-01-01T00:00:00Z
review text: The author considers a parametric model for a random variable X with a density p(x,\(\theta\),\(\Phi\)), where \(\theta\) is a vector-valued parameter of interest and \(\Phi\) a vector-valued nuisance parameter. He obtains relations between the total Fisher information on \(\theta\) and the Fisher information in a statistic S(X) whose distribution depends only on \(\theta\). Under the regularity conditions it is shown that if S(X) is weakly partially sufficient, it has no loss of information. He also considers the generalized Fisher information, and obtains similar results to the above. Some examples are given.
Mathematics Subject Classification ID: 62B05
Mathematics Subject Classification ID: 62B10
zbMATH DE Number: 4215142
zbMATH Keywords: matrix generalizations
zbMATH Keywords: weak partial sufficiency
zbMATH Keywords: completeness
zbMATH Keywords: partial sufficiency in the complete sense
zbMATH Keywords: parametric model
zbMATH Keywords: vector-valued nuisance parameter
zbMATH Keywords: Fisher information
zbMATH Keywords: loss of information
zbMATH Keywords: generalized Fisher information
reviewed by: Masafumi Akahira
MaRDI profile type: Publication
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full work available at URL: 0378-3758(91)90025-a
OpenAlex ID: W2050137667
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description: scientific article; zbMATH DE number 4215142