Estimating the asymptotic variance of generalized L-statistics

Mary E. Putt, Vernon M. Chinchilli

Research output: Contribution to journalArticle

Abstract

Strong convergence of the estimated asymptotic variance (σ2(Ta(HN))) of generalized L-statistics is demonstrated for smooth and discrete weighting functions. For smooth weighting functions that are trimmed, such as the 25%-trimmed mean, and for discrete functions, such as the median, minimal conditions are required for strong convergence of σ2(Ta(HN)). In a simulation study, σ2(Ta(HN)) for the trimmed mean, but not the median, appeared to converge to the sample variance of the statistic for samples from three distributions (normal, contaminated normal and Cauchy). For the smallest sample in the study (n = 16), σ2(Ta(HN)) tended to underestimate the sample variance of the GL-statistics.

Original languageEnglish (US)
Pages (from-to)733-751
Number of pages19
JournalCommunications in Statistics - Theory and Methods
Volume31
Issue number5
DOIs
StatePublished - May 2002

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

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