# Some applications of probability generating function based methods to statistical estimation

Discussiones Mathematicae Probability and Statistics (2009)

- Volume: 29, Issue: 2, page 131-153
- ISSN: 1509-9423

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topManuel L. Esquível. "Some applications of probability generating function based methods to statistical estimation." Discussiones Mathematicae Probability and Statistics 29.2 (2009): 131-153. <http://eudml.org/doc/277064>.

@article{ManuelL2009,

abstract = {After recalling previous work on probability generating functions for real valued random variables we extend to these random variables uniform laws of large numbers and functional limit theorem for the empirical probability generating function. We present an application to the study of continuous laws, namely, estimation of parameters of Gaussian, gamma and uniform laws by means of a minimum contrast estimator that uses the empirical probability generating function of the sample. We test the procedure by simulation and we prove the consistency of the estimator.},

author = {Manuel L. Esquível},

journal = {Discussiones Mathematicae Probability and Statistics},

keywords = {probability generating function; empirical laws; estimation of parameters of continuous laws},

language = {eng},

number = {2},

pages = {131-153},

title = {Some applications of probability generating function based methods to statistical estimation},

url = {http://eudml.org/doc/277064},

volume = {29},

year = {2009},

}

TY - JOUR

AU - Manuel L. Esquível

TI - Some applications of probability generating function based methods to statistical estimation

JO - Discussiones Mathematicae Probability and Statistics

PY - 2009

VL - 29

IS - 2

SP - 131

EP - 153

AB - After recalling previous work on probability generating functions for real valued random variables we extend to these random variables uniform laws of large numbers and functional limit theorem for the empirical probability generating function. We present an application to the study of continuous laws, namely, estimation of parameters of Gaussian, gamma and uniform laws by means of a minimum contrast estimator that uses the empirical probability generating function of the sample. We test the procedure by simulation and we prove the consistency of the estimator.

LA - eng

KW - probability generating function; empirical laws; estimation of parameters of continuous laws

UR - http://eudml.org/doc/277064

ER -

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