Search results for "Distribution fitting"
showing 3 items of 3 documents
Quantile estimation via distribution fitting
2019
This paper focuses on nonparametric estimation of quantiles, based on estimators of the distribution function. We review some known and recommended quantile estimators and propose a new one, which has all the desired properties of quantile estimators. The consistency and asymptotic normality of the estimators is proved. The estimators considered are compared in a small simulation study.
Strength distribution in paper
1998
Abstract Tensile strength distributions are studied in four paper samples that exhibit a variety of brittle-to-ductile properties. 1005 tensile specimens were measured in each case. The standard Gumbel and Weibull distributions, and a recently proposed double exponential modification of the former are compared with the observations visually and using chi-squared and Kolmogorov–Smirnov tests. The Gumbel distribution fails to fit the data while the Weibull distribution gives satisfactory agreement. However, the double exponential distribution fits the data best, regardless of the ductility of the material.
A Software Tool for the Exponential Power Distribution: The normalp Package
2005
In this paper we present the normalp package, a package for the statistical environment R that has a set of tools for dealing with the exponential power distribution. In this package there are functions to compute the density function, the distribution function and the quantiles from an exponential power distribution and to generate pseudo-random numbers from the same distribution. Moreover, methods concerning the estimation of the distribution parameters are described and implemented. It is also possible to estimate linear regression models when we assume the random errors distributed according to an exponential power distribution. A set of functions is designed to perform simulation studi…