Unbiased estimators of multivariate discrete distributions and chi-square goodness-of-fit test.

Mikhail S. Nikulin; Vassiliy G. Voinov

Qüestiió (1993)

  • Volume: 17, Issue: 3, page 301-326
  • ISSN: 0210-8054

Abstract

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We consider the problem of estimation of the value of a real-valued function u(θ), θ = (θ1, ..., θk)T, on the basis of a sample from non-truncated or truncated multivariate Modified Power Series Distributions. Using the general theory of estimation and the results of Patil (1965) and Patel (1978) we give the tables of MVUE's for functions of parameter θ of trinomial, multinomial, negative-multinomial and left-truncated modified power series distributions. We have applied the properties of MVUE's and the results from the theory of MVU estimation to construct a goodness-of-fit chi-squared test for multivariate modified power series distributions.

How to cite

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Nikulin, Mikhail S., and Voinov, Vassiliy G.. "Unbiased estimators of multivariate discrete distributions and chi-square goodness-of-fit test.." Qüestiió 17.3 (1993): 301-326. <http://eudml.org/doc/40093>.

@article{Nikulin1993,
abstract = {We consider the problem of estimation of the value of a real-valued function u(θ), θ = (θ1, ..., θk)T, on the basis of a sample from non-truncated or truncated multivariate Modified Power Series Distributions. Using the general theory of estimation and the results of Patil (1965) and Patel (1978) we give the tables of MVUE's for functions of parameter θ of trinomial, multinomial, negative-multinomial and left-truncated modified power series distributions. We have applied the properties of MVUE's and the results from the theory of MVU estimation to construct a goodness-of-fit chi-squared test for multivariate modified power series distributions.},
author = {Nikulin, Mikhail S., Voinov, Vassiliy G.},
journal = {Qüestiió},
keywords = {multivariate modified power series distributions; sufficient statistic; MVUE; Rao-Kolmogorov-Blackwell method; -squared goodness-of-fit test; minimum -squared estimator; maximum likelihood estimator; Chernoff-Lehmann theorem; BAN estimator},
language = {eng},
number = {3},
pages = {301-326},
title = {Unbiased estimators of multivariate discrete distributions and chi-square goodness-of-fit test.},
url = {http://eudml.org/doc/40093},
volume = {17},
year = {1993},
}

TY - JOUR
AU - Nikulin, Mikhail S.
AU - Voinov, Vassiliy G.
TI - Unbiased estimators of multivariate discrete distributions and chi-square goodness-of-fit test.
JO - Qüestiió
PY - 1993
VL - 17
IS - 3
SP - 301
EP - 326
AB - We consider the problem of estimation of the value of a real-valued function u(θ), θ = (θ1, ..., θk)T, on the basis of a sample from non-truncated or truncated multivariate Modified Power Series Distributions. Using the general theory of estimation and the results of Patil (1965) and Patel (1978) we give the tables of MVUE's for functions of parameter θ of trinomial, multinomial, negative-multinomial and left-truncated modified power series distributions. We have applied the properties of MVUE's and the results from the theory of MVU estimation to construct a goodness-of-fit chi-squared test for multivariate modified power series distributions.
LA - eng
KW - multivariate modified power series distributions; sufficient statistic; MVUE; Rao-Kolmogorov-Blackwell method; -squared goodness-of-fit test; minimum -squared estimator; maximum likelihood estimator; Chernoff-Lehmann theorem; BAN estimator
UR - http://eudml.org/doc/40093
ER -

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