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

Page 1

Displaying 1 – 7 of 7

Showing per page

Bad luck in quadratic improvement of the linear estimator in a special linear model

Gejza Wimmer (1998)

Applications of Mathematics

The paper concludes our investigations in looking for the locally best linear-quadratic estimators of mean value parameters and of the covariance matrix elements in a special structure of the linear model (2 variables case) where the dispersions of the observed quantities depend on the mean value parameters. Unfortunately there exists no linear-quadratic improvement of the linear estimator of mean value parameters in this model.

Bayes unbiased estimators of parameters of linear trend with autoregressive errors

František Štulajter (1987)

Aplikace matematiky

The method of least wquares is usually used in a linear regression model 𝐘 = 𝐗 β + ϵ for estimating unknown parameters β . The case when ϵ is an autoregressive process of the first order and the matrix 𝐗 corresponds to a linear trend is studied and the Bayes approach is used for estimating the parameters β . Unbiased Bayes estimators are derived for the case of a small number of observations. These estimators are compared with the locally best unbiased ones and with the usual least squares estimators.

Bayesian inference in group judgement formulation and decision making using qualitative controlled feedback.

S. James Press (1980)

Trabajos de Estadística e Investigación Operativa

This paper considers the problem of making statistical inferences about group judgements and group decisions using Qualitative Controlled Feedback, from the Bayesian point of view. The qualitative controlled feedback procedure was first introduced by Press (1978), for a single question of interest. The procedure in first reviewed here including the extension of the model to the multiple question case. We develop a model for responses of the panel on each stage. Many questions are treated simultaneously...

Bayesian joint modelling of the mean and covariance structures for normal longitudinal data.

Edilberto Cepeda-Cuervo, Vicente Nunez-Anton (2007)

SORT

We consider the joint modelling of the mean and covariance structures for the general antedependence model, estimating their parameters and the innovation variances in a longitudinal data context. We propose a new and computationally efficient classic estimation method based on the Fisher scoring algorithm to obtain the maximum likelihood estimates of the parameters. In addition, we also propose a new and innovative Bayesian methodology based on the Gibbs sampling, properly adapted for longitudinal...

Bias correction on censored least squares regression models

Jesus Orbe, Vicente Núñez-Antón (2012)

Kybernetika

This paper proposes a bias reduction of the coefficients' estimator for linear regression models when observations are randomly censored and the error distribution is unknown. The proposed bias correction is applied to the weighted least squares estimator proposed by Stute [28] [W. Stute: Consistent estimation under random censorship when covariables are present. J. Multivariate Anal. 45 (1993), 89-103.], and it is based on model-based bootstrap resampling techniques that also allow us to work with...

Currently displaying 1 – 7 of 7

Page 1