method of moments estimator for geometric distribution

METHOD OF MOMENTS ESTIMATOR FOR GEOMETRIC DISTRIBUTION HOW TO

The first part of the present paper shows how to estimate the parameter of truncated geometric distribution as a true probability model, by method of moment. also treated the truncated binomial and negative binomial distribution and truncated Poisson distribution and has shown how to estimate the parameter of distributions. has treated the truncated binomial distribution. Several studies have been made of truncated distribution. Keywords:Truncated Geometric Bootstrap Method, Stationary Process, Moving Block and Geometric Stationary Bootstrap Method The mean and variance were estimated for the truncated geometric distribution and the bootstrap algorithm developed based on the proposed probability model.

The method was able to determine the block sizes b and probability p attached to its random selections. This probability model was used in resampling blocks of random length, where the length of each blocks has a truncated geometric distribution. We estimate the parameters of a geometric distribution which has been truncated as a probability model for the bootstrap algorithm. This paper introduced a bootstrap method called truncated geometric bootstrap method for time series stationary process. Received 28 April 2014 revised accepted 10 June 2014 This work is licensed under the Creative Commons Attribution International License (CC BY). Department of Mathematical Science, Olabisi Onabanjo University, Ago-Iwoye, NigeriaĮmail: © 2014 by author and Scientific Research Publishing Inc.

Method of moments estimator for geometric distribution