THERMAL SCIENCE
International Scientific Journal
GOODNESS-OF-FIT TESTS FOR THE BETA GOMPERTZ DISTRIBUTION
ABSTRACT
This article studied the goodness-of-fit tests for the beta Gompertz distribution with four parameters based on a complete sample. The parameters were estimated by the maximum likelihood method. Critical values were found by Monte Carlo simulation for the modified Kolmogorov-Smirnov, Anderson-Darling, Cramer-von Mises, and Lilliefors test statistics. The power of these test statistics founded the optimal alternative distribution. Real data applications were used as examples for the goodness of fit tests.
KEYWORDS
PAPER SUBMITTED: 2020-05-01
PAPER REVISED: 2020-05-28
PAPER ACCEPTED: 2020-06-01
PUBLISHED ONLINE: 2020-10-25
THERMAL SCIENCE YEAR
2020, VOLUME
24, ISSUE
Supplement 1, PAGES [S69 - S81]
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