All a b c d e f g h i j k l m n o p q r s t u v w x y z Other

Previous Page 3

Displaying 41 – 53 of 53

Showing per page

An admissible estimator of a lower-bounded scale parameter under squared-log error loss function

Eisa Mahmoudi, Hojatollah Zakerzadeh (2011)

Kybernetika

Estimation in truncated parameter space is one of the most important features in statistical inference, because the frequently used criterion of unbiasedness is useless, since no unbiased estimator exists in general. So, other optimally criteria such as admissibility and minimaxity have to be looked for among others. In this paper we consider a subclass of the exponential families of distributions. Bayes estimator of a lower-bounded scale parameter, under the squared-log error loss function with...

An alternative analysis of variance.

Nicholas T. Longford (2008)

SORT

The one-way analysis of variance is a staple of elementary statistics courses. The hypothesis test of homogeneity of the means encourages the use of the selected-model based estimators which are usually assessed without any regard for the uncertainty about the outcome of the test. We expose the weaknesses of such estimators when the uncertainty is taken into account, as it should be, and propose synthetic estimators as an alternative.

An exploratory canonical analysis approach for multinomial populations based on the φ -divergence measure

Julio A. Pardo, Leandro Pardo, María Del Carmen Pardo, K. Zografos (2004)

Kybernetika

In this paper we consider an exploratory canonical analysis approach for multinomial population based on the φ -divergence measure. We define the restricted minimum φ -divergence estimator, which is seen to be a generalization of the restricted maximum likelihood estimator. This estimator is then used in φ -divergence goodness-of-fit statistics which is the basis of two new families of statistics for solving the problem of selecting the number of significant correlations as well as the appropriateness...

Analysis on the individual efficiency prediction in the composed error frontier model. A Monte Carlo study.

Rafaela Dios Palomares, Antonio Ramos Millán, José Angel Roldán-Casas (2002)

Qüestiió

This study seeks to analyse some important questions related to the Stochastic Frontier Model, such as the method proposed by Jondrow et al (1982) to separate the error term into its two components, and the measure of efficiency given by Timmer (1971). To this purpose, a Monte Carlo experiment has been carried out using the Half-Normal and Normal-Exponential specifications throughout the rank of the γ parameter. The estimation errors have been eliminated, so that the intrinsic variability of the...

Approximate bias for first-order autoregressive model with uniform innovations. Small sample case

Karima Nouali, Hocine Fellag (2002)

Discussiones Mathematicae Probability and Statistics

The first-order autoregressive model with uniform innovations is considered. The approximate bias of the maximum likelihood estimator (MLE) of the parameter is obtained. Also, a formula for the approximate bias is given when a single outlier occurs at a specified time with a known amplitude. Simulation procedures confirm that our formulas are suitable. A small sample case is considered only.

Currently displaying 41 – 53 of 53

Previous Page 3