The Annals of Mathematical Statistics

Estimating the Mean and Variance of Normal Populations from Singly Truncated and Doubly Truncated Samples

A. C. Cohen

Full-text: Open access

Abstract

This paper is concerned with the problem of estimating the mean and variance of normal populations from singly and doubly truncated samples having known truncation points. Maximum likelihood estimating equations are derived which, with the aid of standard tables of areas and ordinates of the normal frequency function, can be readily solved by simple iterative processes. Asymptotic variances and covariances of these estimates are obtained from the information matrices. Numerical examples are given which illustrate the practical application of these results. In Sections 3 to 8 inclusive, the following cases of doubly truncated samples are considered: I, number of unmeasured observations unknown; II, number of unmeasured observations in each `tail' known; and III, total number of unmeasured observations known, but not the number in each `tail'. In Section 9, singly truncated samples are treated as special cases of I and II above.

Article information

Source
Ann. Math. Statist. Volume 21, Number 4 (1950), 557-569.

Dates
First available in Project Euclid: 28 April 2007

Permanent link to this document
http://projecteuclid.org/euclid.aoms/1177729751

JSTOR
links.jstor.org

Digital Object Identifier
doi:10.1214/aoms/1177729751

Mathematical Reviews number (MathSciNet)
MR38041

Citation

Cohen, A. C. Estimating the Mean and Variance of Normal Populations from Singly Truncated and Doubly Truncated Samples. The Annals of Mathematical Statistics 21 (1950), no. 4, 557--569. doi:10.1214/aoms/1177729751. http://projecteuclid.org/euclid.aoms/1177729751.


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