Simulation of Daily Precipitation Data Using Nonhomogeneous Markov Model I -Theory
Young‐Il Moon, Young-Il Cha · Journal of the Korean Society of Civil Engineers · 2004
This paper presents nonhomogeneous transition probabilities to describe nonhomogeneous status based on nonhomogeneous Markov chain's systematic concept using a expanded nonparametric kernel density function method. The daily transition probability matrices are estimated nonparametrically. A kernel estimator is used to estimate the transition probabilities through the weighted average of transition counts over a symmetric time interval centered at the day of interest. Thus, a wet day is decided by the nonhomogeneous transition probabilities. The precipitation amounts on each days of interests are decided form the kernel density function estimated from all wet days that fall within a time interval centered on the calendar day of interest over all the years of historical observations.