Best-Fit Probability Models for Maximum Monthly Rainfall in Bangladesh Using Gaussian Mixture Distributions

In this study, Gaussian/normal distributions (N) and mixtures of two normal (N2), three normal (N3), four normal (N4), or five normal (N5) distributions were applied to data with extreme values for precipitation for 35 weather stations in Bangladesh. For parameter estimation, maximum likelihood estimation was applied by using an expectation-maximization algorithm. For selecting the best-fit model, graphical inspection (probability density function (pdf), cumulative density function (cdf), quantile-quantile (Q-Q) plot) and numerical criteria (Akaike’s information criterion (AIC), Bayesian information criterion (BIC), root mean square percentage error (RMSPE)) were used. In most of the cases, AIC and BIC gave the same best-fit results but their RMSPE results differed. The best-fit result of each station was chosen as the distribution with the lowest…