Tests of fit for a lognormal distribution

作者：Batsidis A; Economou P^*; Tzavelas G

来源：Journal of Statistical Computation and Simulation, 2016, 86(2): 215-235.

DOI：10.1080/00949655.2014.1003138

• Kullback-Leibler
• weighted distribution
• goodness-of-fit tests
• Monte Carlo simulation

The problem of goodness of fit of a lognormal distribution is usually reduced to testing goodness of fit of the logarithmic data to a normal distribution. In this paper, new goodness-of-fit tests for a lognormal distribution are proposed. The new procedures make use of a characterization property of the lognormal distribution which states that the Kullback-Leibler measure of divergence between a probability density p.d.f) and its r-size weighted p.d.f is symmetric only for the lognormal distribution [Tzavelas G, Economou P. Characterization properties of the log-normal distribution obtained with the help of divergence measures. Stat Probab Lett. 2012;82(10):1837-1840]. A simulation study examines the performance of the new procedures in comparison with existing goodness-of-fit tests for the lognormal distribution. Finally, two well-known data sets are used to illustrate the methods developed.

• 出版日期2016-1-22