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El sesgo condicionado en el análisis de influencia: una revisión.

Juan Manuel Muñoz Pichardo, Juan Luis Moreno Rebollo, M. Teresa Gómez Gómez, Alicia Enguix González (2001)

Qüestiió

El sesgo condicionado se ha propuesto como diagnóstico de influencia en distintos modelos y técnicas estadísticas. Tratando de recoger una visión global de la utilidad del concepto, en este trabajo se hace una revisión general del mismo relacionándolo con la curva de sensibilidad y la curva de influencia muestral. Además, se señalan posibles líneas de trabajo que permitirán abordar el análisis de la influencia a través de este enfoque en una gran variedad de técnicas estadísticas.

Eleccions a Girona: un exemple d'estudi d'una taula ternària.

F. Borrell Thió (1996)

Qüestiió

El artículo muestra una parte de los resultados obtenidos en una aplicación del Análisis Factorial Múltiple al estudio de una tabla ternaria de contingencia. No se pretende proporcionar una interpretación exhaustiva de los resultados electorales, sino resaltar que, en este estudio, los dos tipos de inercia en que se descompone la inercia total de la tabla (Inercia INTER e inercia INTRA) son casi ortogonales, lo que facilita mucho su interpretación. Por este motivo este ejemplo puede utilizarse dentro...

Eliminating transformations for nuisance parameters in linear regression models with type I constraints

Pavla Kunderová (2007)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

The linear regression model in which the vector of the first order parameter is divided into two parts: to the vector of the useful parameters and to the vector of the nuisance parameters is considered. The type I constraints are given on the useful parameters. We examine eliminating transformations which eliminate the nuisance parameters without loss of information on the useful parameters.

Empirical analysis of current status data for additive hazards model with auxiliary covariates

Jianling Zhang, Mei Yang, Xiuqing Zhou (2021)

Kybernetika

In practice, it often occurs that some covariates of interest are not measured because of various reasons, but there may exist some auxiliary information available. In this case, an issue of interest is how to make use of the available auxiliary information for statistical analysis. This paper discusses statistical inference problems in the context of current status data arising from an additive hazards model with auxiliary covariates. An empirical log-likelihood ratio statistic for the regression...

Empirical approximation in Markov games under unbounded payoff: discounted and average criteria

Fernando Luque-Vásquez, J. Adolfo Minjárez-Sosa (2017)

Kybernetika

This work deals with a class of discrete-time zero-sum Markov games whose state process x t evolves according to the equation x t + 1 = F ( x t , a t , b t , ξ t ) , where a t and b t represent the actions of player 1 and 2, respectively, and ξ t is a sequence of independent and identically distributed random variables with unknown distribution θ . Assuming possibly unbounded payoff, and using the empirical distribution to estimate θ , we introduce approximation schemes for the value of the game as well as for optimal strategies considering both,...

Empirical comparison between the Nelson-Aalen Estimator and the Naive Local Constant Estimator.

Ana María Pérez-Marín (2008)

SORT

The Nelson-Aalen estimator is widely used in biostatistics as a non-parametric estimator of the cumulative hazard function based on a right censored sample. A number of alternative estimators can be mentioned, namely, the naive local constant estimator (Guillén, Nielsen and Pérez-Marín, 2007) which provides improved bias versus variance properties compared to the traditional Nelson-Aalen estimator. Nevertheless, an empirical comparison of these two estimators has never been carried out. In this...

Empirical estimator of the regularity index of a probability measure

Alain Berlinet, Rémi Servien (2012)

Kybernetika

The index of regularity of a measure was introduced by Beirlant, Berlinet and Biau [1] to solve practical problems in nearest neighbour density estimation such as removing bias or selecting the number of neighbours. These authors proved the weak consistency of an estimator based on the nearest neighbour density estimator. In this paper, we study an empirical version of the regularity index and give sufficient conditions for its weak and strong convergence without assuming absolute continuity or...

Empirical likelihood for quantile regression models with response data missing at random

S. Luo, Shuxia Pang (2017)

Open Mathematics

This paper studies quantile linear regression models with response data missing at random. A quantile empirical-likelihood-based method is proposed firstly to study a quantile linear regression model with response data missing at random. It follows that a class of quantile empirical log-likelihood ratios including quantile empirical likelihood ratio with complete-case data, weighted quantile empirical likelihood ratio and imputed quantile empirical likelihood ratio are defined for the regression...

Empirical regression quantile processes

Jana Jurečková, Jan Picek, Martin Schindler (2020)

Applications of Mathematics

We address the problem of estimating quantile-based statistical functionals, when the measured or controlled entities depend on exogenous variables which are not under our control. As a suitable tool we propose the empirical process of the average regression quantiles. It partially masks the effect of covariates and has other properties convenient for applications, e.g. for coherent risk measures of various types in the situations with covariates.

Empirical significance test of the goodness-of-fit for some pyramidal clustering procedures.

Carles Capdevila Marquès, Antoni Arcas Pons (1995)

Qüestiió

Through a series of simulation tests by Monte Carlo methods, some aspects relating to the inference concerning pyramidal trees built by the maximum and minimum methods are considered. In this sense, the quantiles of the γ-Goodman-Kruskal statistic allow us to tabulate a significance test of the goodness-of-fit of a pyramidal clustering procedure. On the other side, the pyramidal method of maximum is observed to be clearly better (more efficient) than that of the minimum in terms of the expected...

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