Parameter Estimation of Power Function Distribution with TL-moments

Accurate estimation of parameters of a probability distribution is of immense importance in statistics. Biased and imprecise estimation of parameters can lead to erroneous results. Our focus is to estimate the parameter of Power function distribution accurately because this density is now widely used for modelling various types of data.  In this study, L-moments, TL-moments, LL-moments and LH-moments of Power function distribution are derived. In addition, the coefficient of variation, skewness and kurtosis are obtained by method of moments, L-moments and TL-moments. Parameters of the density are estimated using linear moments and compared with method of moments and MLE on the basis of bias, root mean square error and coefficients through simulation study. L-moments proved to be superior for the parameter estimation and this conclusion is equally true for different parametric values and sample size.

• Autores: Naveed-Shahzad, Mirza; Asghar, Zahid; Shehzad, Farrukh; Shahzadi, Mubeen
• Tipo de recurso: Article of journal
• Fecha de publicación: 2015
• Institución: Universidad Nacional de Colombia
• Repositorio: Universidad Nacional de Colombia
• Idioma: spa
• OAI Identifier: oai:repositorio.unal.edu.co:unal/66528
• Acceso en línea: https://repositorio.unal.edu.co/handle/unal/66528; http://bdigital.unal.edu.co/67556/
• Palabra clave: 51 Matemáticas / Mathematics; 31 Colecciones de estadística general / Statistics; Moments; Monte Carlo Simulation; Order Statistics; Parameter estimation; Power function distribution; Distribución de función de potencias; Estadísticas de orden; Estimación de parámetros; Momentos; Simulación de Monte Carlo.
• Rights: openAccess
• License: Atribución-NoComercial 4.0 Internacional