Significance of AIC differences for precipitation intensity distributions

✍ Scribed by Anthony T. Cahill

• Book ID: 104326829
• Publisher: Elsevier Science
• Year: 2003
• Tongue: English
• Weight: 150 KB
• Volume: 26
• Category: Article
• ISSN: 0309-1708
• DOI: 10.1016/s0309-1708(02)00167-7

✦ Synopsis

Chain dependent models for daily precipitation typically model the occurrence process as a Markov chain and the precipitation intensity process using one of several probability distributions. It has been argued that the mixed exponential distribution is a superior model for the rainfall intensity process, since the value of its information criterion (Akaike information criterion or Bayesian information criterion) when fit to precipitation data is usually less than the more commonly used gamma distribution. The differences between the criterion values of the best and lesser models are generally small relative to the magnitude of the criterion value, which raises the question of whether these differences are statistically significant. Using a likelihood ratio statistic and nesting the gamma and mixed exponential distributions in a parent distribution, we show indirectly that generally the superiority of the mixed exponential distribution over the gamma distribution for modeling precipitation intensity is statistically significant. Comparisons are also made with a common-a gamma model, which are less informative.