On the K OLMOGOROV ‐S MIRNOV  Test for the P OISSON  Distribution with Unknown Mean | Zendy

Campbell D. B. | Zendy; Oprian C. A. | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Premium

On the K OLMOGOROV ‐S MIRNOV Test for the P OISSON Distribution with Unknown Mean

Author(s) -

Campbell D. B.,

Oprian C. A.

Publication year - 1979

Publication title -

biometrical journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.108

H-Index - 63

eISSN - 1521-4036

pISSN - 0323-3847

DOI - 10.1002/bimj.4710210104

Subject(s) - table (database) , statistics , statistic , distribution (mathematics) , combinatorics , sample (material) , set (abstract data type) , mathematics , monte carlo method , computer science , chemistry , chromatography , mathematical analysis , data mining , programming language

The standard tables for the K OLMOGOROV ‐S MIRNOV test are valid only in the case of testing whether a set of observations is from a completely specified cumulative distribution, F 0 ( X ), with all parameters known. If the parameters are unknown and must be estimated from the sample, then the tables are not valid. A table is given in this paper for use with the K OLMOGOROV ‐S MIRNOV statistic in the case of testing whether a set of observations is from the P OISSON distribution with an unknown mean that must be estimated from the sample. The table is obtained from a Monte Carlo calculation.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here

Accelerating Research