Displaying similar documents to “Assessing influence in survival data with a cured fraction and covariates.”

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

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

SORT

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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...

Bayes estimation of the reliability function and hazard rate of a Weibull failure time distribution.

Sanjoy K. Sinha (1986)

Trabajos de Estadística

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Given the recorded life times from a Weibull distribution, Bayes estimates of the reliability function and hazard rate are obtained using the posterior distributions and some recent results on Bayesian approximations due to Lindley (1980). Based on a Monte Carlo study, these estimates are compared with their maximum likelihood counterparts.

A comparison of parametric models for mortality graduation. Application to mortality data for the Valencia Region (Spain).

Ana Debón, Francisco Montes, Ramón Sala (2005)

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The parametric graduation of mortality data has as its objective the satisfactory estimation of the death rates based on mortality data but using an age-dependent function whose parameters are adjusted from the crude rates obtainable directly from the data. This paper proposes a revision of the most commonly used parametric models and compares the result obtained with each of them when they are applied to the mortality data for the Valencia Region. As a result of the comparison, we conclude...

Likelihood and the Bayes procedure.

Hirotugu Akaike (1980)

Trabajos de Estadística e Investigación Operativa

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In this paper the likelihood function is considered to be the primary source of the objectivity of a Bayesian method. The necessity of using the expected behaviour of the likelihood function for the choice of the prior distribution is emphasized. Numerical examples, including seasonal adjustment of time series, are given to illustrate the practical utility of the common-sense approach to Bayesian statistics proposed in this paper.

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

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

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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...

Change-Point problems: approaches and applications.

Adrian F. M. Smith (1980)

Trabajos de Estadística e Investigación Operativa

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Problems of making inferences about abrupt changes in the mechanism underlying a sequence of observations are considered in both retrospective and on-line contexts. Among the topics considered are the Lindisfarne scribes problem; switching straight lines; manoeuvering targets, and shifts of level or slope in linear time series models. Summary analyses of data obtained in studies of schizophrenic and kidney transplant patients are presented.

Factor analysis and information criteria.

Michele Costa (1996)

Qüestiió

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In this paper the research of the true number of latent factors in exploratoty factor analysis model is studied through a comparison between the log likelihood ratio test statistics, the information criteria of Akaike, Schwarz and Hannah-Quinn and a procedure of cross-validation. In a simulation study the a priori knowledge of the exact factor structure is used to evaluate the goodness of the different methods.

Likelihood for random-effect models (with discussion).

Youngjo Lee, John A. Nelder (2005)

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For inferences from random-effect models Lee and Nelder (1996) proposed to use hierarchical likelihood (h-likelihood). It allows influence from models that may include both fixed and random parameters. Because of the presence of unobserved random variables h-likelihood is not a likelihood in the Fisherian sense. The Fisher likelihood framework has advantages such as generality of application, statistical and computational efficiency. We introduce an extended likelihood framework and...