Estimation of Mean Rain Rate through Censoring

Abstract

A mixed lognormal distribution is fit to rain-rate data to estimate the space?time average. To mitigate problems associated with biased data, data below a minimum and above a maximum threshold are treated as if they are at the respective threshold, and thus in a sense, are censored. The asymptotic variability of the estimate is computed using Fisher information. Computations of asymptotic variance over a portion of the parameter space show that estimates from censored data are more efficient than those from the minimum chi-square and least squares methods. The censoring, minimum chi-square, and least square methods are applied to simulated data to illustrate their usefulness in estimating rain rate.