Significance of AIC differences for precipitation intensity distributions |
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| Institution: | 1. Departament d’Enginyeria Rural i Agroalimentària, Universitat Politècnica de València, c/Camí de Vera s/n, 46022 València, Spain;2. Departament d’Estadística i Investigació Operativa Aplicades i Qualitat, Universitat Politècnica de València, c/Camí de Vera s/n, 46022 València, Spain;3. IFAPA, Centro Las Torres-Tomejil, Ctra. Sevilla-Cazalla, km 12.2, 41200 Alcalá del Río, Sevilla, Spain;4. Programa d’Ús Eficient de l’Aigua, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Edifici Fruitcentre, Parc de Gardeny, 25003 Lleida, Spain;1. Water Engineering Department, Faculty of Agriculture, University of Tabriz, Tabriz, Iran;2. Programa d’Ús Eficient de l’Aigua, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Edifici Fruitcentre, Parc de Gardeny, 25003 Lleida, Spain;3. Civil Engineering Department, Architecture and Engineering Faculty, Canik Basari University, Samsun, Turkey;4. NEIKER, AB. Basque Country Research Institute for Agricultural Development, Alava, Spain;1. School of Kinesiology and Health Studies, SKHS Building, 28 Division Street, Queen''s University, Kingston, Ontario, K7L 3N6, Canada;2. Department of Kinesiology, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, N2L 3G1, Canada |
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| Abstract: | 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. |
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