Likelihood functions and some maximum likelihood estimators for symbolic data

被引：30

作者：

Le-Rademacher, J. ^{[1
]}

Billard, L. ^{[2
]}

机构：

[1] Med Coll Wisconsin, Div Biostat, Milwaukee, WI 53226 USA

[2] Univ Georgia, Dept Stat, Athens, GA 30602 USA

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 2011年 / 141卷 / 04期

基金：

美国国家科学基金会;

关键词：

Symbolic data analysis; Likelihood functions; Maximum likelihood estimators; Interval-valued data; Histogram-valued data; Triangular-distribution-valued data; DESCRIPTIVE STATISTICS; GALOIS LATTICES; CAPACITIES; KNOWLEDGE; OBJECTS;

D O I：

10.1016/j.jspi.2010.11.016

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Likelihood functions are the foundation of many statistical methodologies in classical data analysis. Likelihood functions for symbolic data must be introduced before these classical methods can be extended to the analysis of symbolic data. In this paper, we propose the likelihood function for symbolic data and illustrate its applications by finding the maximum likelihood estimators for the mean and the variance of three common types of symbolic-valued random variables: interval-valued, histogram-valued and triangular-distribution-valued variables. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：1593 / 1602

页数：10

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