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Inference on the location parameter of exponential populations

Maria de Fátima Brilhante, Sandra Mendonça, Dinis Duarte Pestana, Maria Luísa Rocha (2009)

Discussiones Mathematicae Probability and Statistics

Studentization and analysis of variance are simple in Gaussian families because X̅ and S² are independent random variables. We exploit the independence of the spacings in exponential populations with location λ and scale δ to develop simple ways of dealing with inference on the location parameter, namely by developing an analysis of scale in the homocedastic independent k-sample problem.

Inferencia bayesiana en mixturas: métodos aproximados.

Enrique Caro, Juan Ignacio Domínguez, Francisco Javier Girón (1991)

Trabajos de Estadística

The problem of approximating mixtures of distributions has received considerable attention recently. In this paper we consider problems of estimating the mixing proportions of a finite mixture from a Bayesian perspective. The problems which arise from this methodology are basically approximations of finite measures of distributions. We propose two approximating methods and prove that under certain conditions both methods are asymptotically equivalent to a third method, which turns out to be simpler...

Inferring the residual waiting time for binary stationary time series

Gusztáv Morvai, Benjamin Weiss (2014)

Kybernetika

For a binary stationary time series define σ n to be the number of consecutive ones up to the first zero encountered after time n , and consider the problem of estimating the conditional distribution and conditional expectation of σ n after one has observed the first n outputs. We present a sequence of stopping times and universal estimators for these quantities which are pointwise consistent for all ergodic binary stationary processes. In case the process is a renewal process with zero the renewal state...

Influence diagnostics in exponentiated-Weibull regression models with censored data.

Edwin M. M. Ortega, Vicente G. Cancho, Heleno Bolfarine (2006)

SORT

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from the error assumptions and the presence of outliers and influential observations with the fitted models. The literature provides plenty of approaches for detecting outlying or influential observations in data sets. In this paper, we follow the local influence approach (Cook 1986) in detecting influential observations with exponentiated-Weibull regression models. The relevance of the...

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