Displaying similar documents to “Unbiased estimators of multivariate discrete distributions and chi-square goodness-of-fit test.”

Estimating median and other quantiles in nonparametric models

Ryszard Zieliński (1995)

Applicationes Mathematicae

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Though widely accepted, in nonparametric models admitting asymmetric distributions the sample median, if n=2k, may be a poor estimator of the population median. Shortcomings of estimators which are not equivariant are presented.

Goodness-of-fit test for the family of logistic distributions.

N. Aguirre, Mikhail S. Nikulin (1994)

Qüestiió

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Chi-squared goodness-of-fit test for the family of logistic distributions id proposed. Different methods of estimation of the unknown parameters θ of the family are compared. The problem of homogeneity is considered.

On the problem of the means of weighted normal populations.

Mikhail S. Nikulin, Vassiliy G. Voinov (1995)

Qüestiió

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An analytical problem, which arises in the statistical problem of comparing the means of two normal distributions, the variances of which -as well as their ratio- are unknown, is well known in the mathematical statistics as the Behrens-Fisher problem. One generalization of the Behrens-Fisher problem and different aspect concerning the estimation of the common mean of several independent normal distributions with different variances are considered and one solution is proposed. ...

Concomitants and linear estimators in an i-dimensional extremal model.

M. Ivette Gomes (1985)

Trabajos de Estadística e Investigación Operativa

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We consider here a multivariate sample X = (X > ... > X), 1 ≤ j ≤ n, where the X, 1 ≤ j ≤ n, are independent i-dimensional extremal vectors with suitable unknown location and scale parameters λ and δ respectively. Being interested in linear estimation of these parameters, we consider the multivariate sample Z, 1 ≤ j ≤ n, of the order statistic of largest values and their concomitants, and the best linear unbiased estimators of λ and δ based on such multivariate sample....