IDENTIFIKASI POLA DISTRIBUSI CURAH HUJAN MAKSIMUM DAN PENDUGAAN PARAMETERNYA MENGGUNAKAN METODE BAYESIAN MARKOV CHAIN MONTE CARLO - Mukid, Moch. Abdul; Wilandari, Yuciana (Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, 2012)
especially for the management of regional water resources. In this study, we not only identify the distribution of maximum rainfall, but also estimate the parameter of its distribution. The research was conducted in the Grobogan District. Maximum rainfall in the district of Grobogan from 2006 to July 2012 was very varied, but over the years have a pattern unlikely to change. Highest maximum rainfall ranged in December, January, February and March while the lowest rainfall maskimum normally be in June, July and August. By using the Kolmogorov-Smirnov test on the significance level of 5% is known that the maximum rainfall from 2006 to 2012 in the District Grobogan follow a normal distribution with a value of D statistics is 0.089. This statistic produces a significance value ​​of 0.518. By using the Bayesian Markov Chain Monte Carlo obtained the value for the parameter mean of normal distribution is 46.269 mm with a standard error reach into 4.005 mm.