BIAS CORRECTING CONFIDENCE-INTERVALS FOR A NEARLY COMMON PROPERTY

被引：4

作者：

CLINE, DBH ^{[1
]}

SPIEGELMAN, CH ^{[1
]}

机构：

[1] TEXAS A&M UNIV SYST, DEPT STAT, COLLEGE STN, TX 77843 USA

来源：

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS | 1991年 / 11卷 / 02期

基金：

美国国家科学基金会;

关键词：

D O I：

10.1016/0169-7439(91)80060-4

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 [计算机科学与技术];

摘要：

Confidence intervals are an important tool. Realistic confidence intervals account for both random errors and systematic errors (bias). We improve the usual method for combining random and systematic errors. The new methods are simple and often result in increased accuracy for confidence interval levels.

引用

页码：131 / 136

页数：6

共 8 条

[1]

[Anonymous], 1979, MONTE CARLO METHODS

[2]

A MINIMAX APPROACH TO COMBINING MEANS, WITH PRACTICAL EXAMPLES [J].

EBERHARDT, KR ;

REEVE, CP ;

SPIEGELMAN, CH .

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 1989, 5 (02) :129-148

[3]

EISENHART C, SEPCIAL PUBLICATION, V300, P69

[4]

EISENHART C, 1971, NBS SPEC PUBL, V343, P509

[5]

KNAFL G, 1984, TECHNOMETRICS, V26, P233

[6]

KOTZ S, 1985, ENCY STAT SCI, V6, P568

[7]

ESTIMATING COMMON MEAN OF SEVERAL NORMAL POPULATIONS [J].

NORWOOD, TE ;

HINKELMANN, K .

ANNALS OF STATISTICS, 1977, 5 (05) :1047-1050

[8]

RAO PSR, 1984, WG COCHRANS IMPACT S, P203

← 1 →