In this paper we use the quantile function to define statistical models. In particular, we present a five-parameter version of the generalized lambda distribution (FPLD). Three alternative methods for estimating its parameters are proposed and their properties are investigated and compared by making use of real and simulated data sets. It will be shown that the proposed model realistically approximates a number of families of probability distributions, has feasible methods for its parameter estimation, and oers an easier way to generate random numbers.

Comparing Estimation Methods for the FPLD

TARSITANO, Agostino
2010-01-01

Abstract

In this paper we use the quantile function to define statistical models. In particular, we present a five-parameter version of the generalized lambda distribution (FPLD). Three alternative methods for estimating its parameters are proposed and their properties are investigated and compared by making use of real and simulated data sets. It will be shown that the proposed model realistically approximates a number of families of probability distributions, has feasible methods for its parameter estimation, and oers an easier way to generate random numbers.
2010
quantile data analysis; controlled random search; fitting distributions
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/122786
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