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Parsimony in modeling daily precipitation
Author(s) -
Katz Richard W.
Publication year - 1979
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr015i006p01628
Subject(s) - markov chain , precipitation , chain (unit) , sequence (biology) , markov chain monte carlo , mathematics , process (computing) , statistics , econometrics , computer science , meteorology , biology , geography , monte carlo method , physics , astronomy , genetics , operating system
Two stochastic models for representing the sequence of daily precipitation amounts at a point, the Markov chain model proposed by Haan et al. [1976] and the chain‐dependent process proposed by Katz [1977 a , 1977 b ], are contrasted. Through a further analysis of daily precipitation data, it is shown that there is a lack of evidence to support the superiority of the Markov chain model over the simpler chain‐dependent process.