文章基本信息

标题：Parameter Estimation of Singh Maddala Distribution by Moments
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作者：Mirza Naveed Shahzad ; Zahid Asghar
期刊名称：International Journal of Advanced Statistics and Probability
电子版ISSN：2307-9045
出版年度：2013
卷号：1
期号：3
页码：121-131
DOI：10.14419/ijasp.v1i3.1206
出版社：Journal of Advanced Computer Science & Technology
摘要：Singh Maddala Distribution is a flexible distribution and mostly used for modeling the income, wage, expenditure and for wealth distribution of a country. To model the density of the income distribution, we have derived L-moments and TL-moments of the SMD in closed form. These moments are used to estimate the scale parameter which is related to the inequality of the income distribution. This study shows that L-moments and TL-moments are better alternatives against conventional moments and estimators of these moments equally applicable for both small and large sample size. Through Monte Carlo simulation study, we find TL-moments estimators provide least bias and smaller Root Mean Square Error of statistic, coefficient of variation, skewness and kurtosis. We also find that TL-moments are superior to L-moments if we are allowed to discord extreme value, otherwise L-moments provide the best fit.