Benjamin Epstein

Tests for the Validity of the Assumption that the Underlying Distribution of Life is Exponential Part I

It is frequently useful to test, on the basis of life test data, whether or not one is justified in assuming that the underlying distribution of life is exponential. This paper, which appears in two parts, describes a number of graphical and analytical procedures for testing this assumption. Part I of the paper contains descriptions of the mathematical and graphical procedures. Part II contains several worked examples.

Tests for the Validity of the Assumption that the Underlying Distribution of Life is Exponential: Part II

Part I of this paper was published in the previous issue of Technometrics, (Vol. 2, No. 1, February 1960). In Part I Dr. Epstein describes several graphical and analytical procedures for testing the assumption that the underlying distribution of life is exponential. This portion of the paper contains numerical examples illustrative of these procedures.

Elements of the Theory of Extreme Values

The theory of extreme values finds many applications in modern technology. This paper is an attempt to unfold the basic elements of the theory. Frequent examples are given to illustrate both derivations and application.

Statistical Life Test Acceptance Procedures

This paper describes statistical methods for testing hypotheses about the mean of an exponential distribution of life. Advantage is taken of the time-ordered nature of life test data to shorten substantially the time required to reach a decision. Replacement, non-replacement, sequential, non-sequential, and truncated procedures are described. Some useful tables are given at the end of the paper.

Comparison of Some Non-Parametric Tests Against Normal Alternatives with an Application to Life Testing*

Abstract * Research sponsored by the Office of Ordnance Research of the U. S. Army under Contract No. DA-20-018-ORD-13272.

Estimation of the Parameters of Two Parameter Exponential Distributions from Censored Samples

In life testing a two parameter exponential distribution is often required to provide an adequate representation of the observed results. Sufficient statistics and interval estimates for the parameters are given for the case of censored data. Numerical examples are provided.