Particle Swarm Optimization Algorithm for the Shortest Confidence Interval Problem

Autor: Cungen Cao, Shang Gao, Zaiyue Zhang
Rok vydání: 2012
Předmět:
Zdroj: Journal of Computers. 7
ISSN: 1796-203X
DOI: 10.4304/jcp.7.8.1809-1816
Popis: Based on the example of constructing a confidence interval for variance, the notion and construction of the shortest confidence interval are put forward. Furthermore, the particle swarm algorithm for this problem is presented to solve this non-linear programming problem. Compared with the confidence interval calculated with traditional method, it has distinct advantage. The optimum results which is used to find the shortest confidence interval of variance and mean variance are given under the confidence level 0.9 and 0.95. The shortest confidence interval about Gamma distribution, Laplace distribution, Weibull distribution and beta distribution are also discussed. Index Terms—mathematical statistics, confidence interval, the shortest interval, particle swarm algorithm
Databáze: OpenAIRE