Estimation of Parameters of Zero-One Processes by Interval Sampling: An Adaptive Strategy

M. Brown, H. Solomon and M. A. Stephens
Additional contact information
M. Brown: City University of New York, New York, New York
H. Solomon: Stanford University, Stanford, California
M. A. Stephens: Simon Fraser University, Burnaby, British Columbia

Operations Research, 1979, vol. 27, issue 3, 606-615

Abstract: We have considered before the problem of estimating the parameters giving the mean time in each stage, for a two-stage Poisson process, when sampling was permitted only at equal intervals. It was impossible to get good results unless the intervals were small. We now propose an adaptive strategy in which the interval is successively halved until a suitable stage is reached; then all samples can be combined to give estimates. The strategy is examined by Monte Carlo methods, and it is shown to give a considerable improvement over the one-stage method. Figures are given to illustrate the results; they can be used also to improve estimates and give confidence intervals. We propose a technique to give an approximate confidence ellipse for the two parameters, which works well for the ranges considered.

Date: 1979
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/opre.27.3.606 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:27:y:1979:i:3:p:606-615

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().