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An efficient rounding‐off rule estimator: Application to daily rainfall time series
Author(s) -
Deidda Roberto
Publication year - 2007
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 - 10.1029/2006wr005409
Subject(s) - estimator , rounding , series (stratigraphy) , parametric statistics , statistics , mathematics , frequentist inference , sampling (signal processing) , rain gauge , discretization , computer science , meteorology , bayesian probability , geography , bayesian inference , geology , mathematical analysis , precipitation , paleontology , filter (signal processing) , computer vision , operating system
An overview of problems and errors arising when fitting parametric distributions and applying goodness of fit tests on samples containing roughly rounded off measurements is first illustrated. The paper then presents the rounding‐off rule estimator (RRE), an original method that allows the estimation of the percentages of rainfall measurements that have been rounded at some potential resolutions. The efficiency of the RRE is evaluated using a wide set of samples drawn by different distributions and rounded off according to different rounding rules. Finally, the RRE is applied on 340 daily rainfall time series collected by the rain gauge network of the Sardinian Hydrological Survey (Italy). In most stations, results revealed the presence of significant percentages of roughly rounded‐off measurements, even at 1 and 5 mm resolutions, rather than at the standard 0.1 or 0.2 mm discretization. The application of the proposed RRE may give important support to perform quality data analyses, to assess and discriminate methods to fit parametric distributions on rounded‐off samples, and to detect if and how the precision of recorded measurements might have changed in long time series used for climatic change studies.