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Modeling income, wage, wealth, expenditure and various other socialvariables have always been an issue of great concern. The Dagum distributionis considered quite handy to model such type of variables. Our focus inthis study is to derive the L-moments and TL-moments of this distributionin closed form. Using L andamp; TL-moments estimators we estimate the scaleparameter which represents the inequality of the income distribution fromthe mean income. Comparing L-moments, TL-moments and conventionalmoments, we observe that the TL-moment estimator has lessbias and rootmean square errors than those of L and conventional estimators consideredin this study. We also find that the TL-moments have smaller root meansquare errors for the coefficients of variation, skewness and kurtosis. Theseresults hold for all sample sizes we have considered in our Monte Carlo simulationstudy.

Tipo de documento: Artículo - Article

Palabras clave: Dagum distribution, L-moments, Method of moments, Parameter estimation, TL-moments





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Revista Colombiana de Estadística Junio 2013, volumen 36, no.
1, pp.
79 a 93 Comparing TL-Moments, L-Moments and Conventional Moments of Dagum Distribution by Simulated data Comparación de momentos TL, momentos L y momentos convencionales de la distribución Dagum mediante datos simulados Mirza Naveed Shahzad1,a , Zahid Asghar2,b 1 Department 2 Department of Statistics, University of Gujrat, Gujrat, Pakistan of Statistics, Quaid-i-Azam University, Islamabad, Pakistan Abstract Modeling income, wage, wealth, expenditure and various other social variables have always been an issue of great concern.
The Dagum distribution is considered quite handy to model such type of variables.
Our focus in this study is to derive the L-moments and TL-moments of this distribution in closed form.
Using L and TL-moments estimators we estimate the scale parameter which represents the inequality of the income distribution from the mean income.
Comparing L-moments, TL-moments and conventional moments, we observe that the TL-moment estimator has lessbias and root mean square errors than those of L and conventional estimators considered in this study.
We also find that the TL-moments have smaller root mean square errors for the coefficients of variation, skewness and kurtosis.
These results hold for all sample sizes we have considered in our Monte Carlo simulation study. Key words: Dagum distribution, L-moments, Method of moments, Parameter estimation, TL-moments. Resumen La modelación de ingresos, salarios, riqueza, gastos y muchas otras variables de tipo social han sido siempre un tema de gran interés.
La distribución Dagum es considerada para modelar este tipo de variables.
Nos centraremos en este artículo en la derivación de los momentos L y los momentos TL de esta distribución de manera cerrada.
Mediante el uso de los estimadores de momentos L y TL, estimamos el parámetro de escala que representa la desigualdad de la distribución de ingresos a partir de la media.
Comparando ...






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