About one problem of Bernoulli and Euler from the theory of statistical estimation.

Mikhaïl Nikulin

SORT (2006)

  • Volume: 30, Issue: 1, page 91-100
  • ISSN: 1696-2281

Abstract

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We consider some results by D. Bernoulli and L. Euler on the method of maximum likelihood in parametric estimation. The statistical analysis is made by considering a parametric family with a shift parameter.

How to cite

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Nikulin, Mikhaïl. "About one problem of Bernoulli and Euler from the theory of statistical estimation.." SORT 30.1 (2006): 91-100. <http://eudml.org/doc/41621>.

@article{Nikulin2006,
abstract = {We consider some results by D. Bernoulli and L. Euler on the method of maximum likelihood in parametric estimation. The statistical analysis is made by considering a parametric family with a shift parameter.},
author = {Nikulin, Mikhaïl},
journal = {SORT},
keywords = {Inferencia paramétrica; Estimación paramétrica; Estimador puntual; Estimadores insesgados; Estimador de máxima verosimilitud; Distribuciones multivariantes; asymptotic normality; sample mean; Bernoulli's estimator; Euler's estimator; maximum likelihood; unbiased estimator},
language = {eng},
number = {1},
pages = {91-100},
title = {About one problem of Bernoulli and Euler from the theory of statistical estimation.},
url = {http://eudml.org/doc/41621},
volume = {30},
year = {2006},
}

TY - JOUR
AU - Nikulin, Mikhaïl
TI - About one problem of Bernoulli and Euler from the theory of statistical estimation.
JO - SORT
PY - 2006
VL - 30
IS - 1
SP - 91
EP - 100
AB - We consider some results by D. Bernoulli and L. Euler on the method of maximum likelihood in parametric estimation. The statistical analysis is made by considering a parametric family with a shift parameter.
LA - eng
KW - Inferencia paramétrica; Estimación paramétrica; Estimador puntual; Estimadores insesgados; Estimador de máxima verosimilitud; Distribuciones multivariantes; asymptotic normality; sample mean; Bernoulli's estimator; Euler's estimator; maximum likelihood; unbiased estimator
UR - http://eudml.org/doc/41621
ER -

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