An application of Cheng's lemma for minimizing the asymptotic variance of best asymptotically normal estimators based on sample quantiles
type: Item
instance of: scholarly article
title: An application of Cheng's lemma for minimizing the asymptotic variance of best asymptotically normal estimators based on sample quantiles
zbMATH Open document ID: 0709.62028
DOI: 10.1016/0378-3758(90)90138-K
author: Steven G. From
published in: Journal of Statistical Planning and Inference
publication date: 1990-01-01T00:00:00Z
Mathematics Subject Classification ID: 62F10
Mathematics Subject Classification ID: 62F12
Mathematics Subject Classification ID: 62G30
zbMATH DE Number: 4166358
zbMATH Keywords: sample quantiles
zbMATH Keywords: BAN-estimators
zbMATH Keywords: optimal spacings of best asymptotically normal estimators
zbMATH Keywords: optimal spacings for non-location, non-scale parameters
zbMATH Keywords: monotone likelihood ratio
zbMATH Keywords: linear failure rate distribution
MaRDI profile type: Publication
Wikidata QID: Q124817355
cites work: A Unified Approach to Choosing Optimum Quantiles for the ABLE's
cites work: A density-quantile function approach to optimal spacing selection
cites work: Optimal Grouping, Spacing, Stratification, and Piecewise Constant Approximation
cites work: Optimal spacing of quantiles for the estimation of the mixing parameters in a mixture of two exponential distributions
cites work: Asymptotic Properties of a Family of Minimum Quantile Distance Estimators
cites work: Q3672893
description: scientific article; zbMATH DE number 4166358