This article discusses statistical models for solar flare interval
distribution in individual active regions. We analyzed solar flare data in 55
active regions that are listed in the GOES soft X-ray flare catalog. We discuss
some problems with a conventional procedure to derive probability density
functions from any data set and propose a new procedure, which uses the maximum
likelihood method and Akaike Information Criterion (AIC) to objectively compare
some competing probability density functions. We found that lognormal and
inverse Gaussian models are more likely models than the exponential model for
solar flare interval distribution in individual active regions. The results
suggest that solar flares do not occur randomly in time; rather, solar flare
intervals appear to be regulated by solar flare mechanisms. We briefly mention
a probabilistic solar flare forecasting method as an application of a solar
flare interval distribution analysis.Comment: 15 pages, 2 figures, 3 tables, accepted for publication in Solar
Physic