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Estimación bayesiana de una función de fiabilidad con conocimiento a priori gamma expendido.

Domingo Morales, Leandro Pardo, Vicente Quesada (1987)

Trabajos de Investigación Operativa

Se plantea el problema de estimar una función de fiabilidad en el contexto bayesiano no paramétrico, pero utilizando técnicas paramétricas de estimación en procesos estocásticos. Se define el proceso gamma extendido, cuyas trayectorias son tasas de azar crecientes cuando se eligen convenientemente los parámetros del proceso. Se obtienen estimadores basados en este proceso, se estudian sus propiedades asintóticas bayesianas, y se termina con un ejemplo de aplicación mediante simulación.

Estimación paramétrica bayesiana no paramétrica de funciones de supervivencia con observaciones parcialmente censuradas.

Domingo Morales, Vicente Quesada, Leandro Pardo (1986)

Trabajos de Estadística

The problem of nonparametric estimation of a survival function based on a partially censored on the right sample is established in a Bayesian context, using parametric Bayesian techniques. Estimates are obtained considering neutral to the right processes, they are particularized to some of them, and their asymptotic properties are studied from a Bayesian point of view. Finally, an application to a Dirichlet process is simulated.

Estimates of reliability for the normal distribution

Jan Hurt (1980)

Aplikace matematiky

The minimum variance unbiased, the maximum likelihood, the Bayes, and the naive estimates of the reliability function of a normal distribution are studied. Their asymptotic normality is proved and asymptotic expansions for both the expectation and the mean squared error are derived. The estimates are then compared using the concept of deficiency. In the end an extensive Monte Carlo study of the estimates in small samples is given.

Estimation of parameters in a network reliability model with spatial dependence

Ian Hepburn Dinwoodie (2010)

ESAIM: Probability and Statistics

An iterative method based on a fixed-point property is proposed for finding maximum likelihood estimators for parameters in a model of network reliability with spatial dependence. The method is shown to converge at a geometric rate under natural conditions on data.

Estimation of parameters in a network reliability model with spatial dependence

Ian Hepburn Dinwoodie (2005)

ESAIM: Probability and Statistics

An iterative method based on a fixed-point property is proposed for finding maximum likelihood estimators for parameters in a model of network reliability with spatial dependence. The method is shown to converge at a geometric rate under natural conditions on data.

Evaluating improvements of records

Tomasz Rychlik (1997)

Applicationes Mathematicae

We evaluate the extreme differences between the consecutive expected record values appearing in an arbitrary i.i.d. sample in the standard deviation units. We also discuss the relevant estimates for parent distributions coming from restricted families and other scale units.

Exact simultaneous location-scale tests for two shifted exponential samples

Amitava Mukherjee, Zhi Lin Chong, Marco Marozzi (2019)

Kybernetika

The failure time distribution for various items often follows a shifted (two-parameter) exponential model and not the traditional (one-parameter) exponential model. The shifted exponential is very useful in practice, in particular in the engineering, biomedical sciences and industrial quality control when modeling time to event or survival data. The open problem of simultaneous testing for differences in origin and scale parameters of two shifted exponential distributions is addressed. Two exact...

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