Efecto de un proceso de poda en algunos coeficientes de asociación derivados del estadístico χ2.
Efficacités comparées de certaines méthodes de prédiction pour un ARMA perturbé
Efficiency and Optimality Properties of a Class of k-Sample Rank Test Against Trend.
Efficient bootstrap simulation: an overview.
Two basic sources of error are associated to the use of bootstrap methods: one is derived from the fact that the true distribution is substituted by a suitable estimate, and the other is simulation errors. Some techniques to reduce or quantify these errors are discussed in this work. Some of them such as importance sampling or antithetic variates are adapted from classical Monte Carlo swindles, whereas others such as the centered and the balanced bootstrap, are more specific. The existence of common...
Efficient estimation of functionals of the spectral density of stationary Gaussian fields
Minimax bounds for the risk function of estimators of functionals of the spectral density of Gaussian fields are obtained. This result is a generalization of a previous result of Khas'minskii and Ibragimov on Gaussian processes. Efficient estimators are then constructed for these functionals. In the case of linear functionals these estimators are given for all dimensions. For non-linear integral functionals, these estimators are constructed for the two and three dimensional problems.
Efficient estimation of functionals of the spectral density of stationary gaussian fields
Efficient estimation under constraints
Efficient robust nonparametric estimation in a semimartingale regression model
The paper considers the problem of robust estimating a periodic function in a continuous time regression model with the dependent disturbances given by a general square integrable semimartingale with an unknown distribution. An example of such a noise is a non-Gaussian Ornstein–Uhlenbeck process with jumps (see (J. R. Stat. Soc. Ser. B Stat. Methodol.63 (2001) 167–241), (Ann. Appl. Probab.18 (2008) 879–908)). An adaptive model selection procedure, based on the weighted least square estimates, is...
Ein asymptotischer Satz über den maximalen Minimalabstand von unabhängigen Zufallsvektoren mit Anwendung auf einen Anpassungstest im Rp und auf der Kugel.
Empirical approximation in Markov games under unbounded payoff: discounted and average criteria
This work deals with a class of discrete-time zero-sum Markov games whose state process evolves according to the equation where and represent the actions of player 1 and 2, respectively, and is a sequence of independent and identically distributed random variables with unknown distribution . Assuming possibly unbounded payoff, and using the empirical distribution to estimate , 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.
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
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
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
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.
Entropy estimate for -monotone functions via small ball probability of integrated Brownian motions.
Equivalence Between Tie-Corrected Spearman Test and a Chi-Square Test in a Fourfold Contingency Table.
Equivalence of exponential decay rates for bootstrap percolation like cellular automata
Estimación bayesiana de una función de fiabilidad con conocimiento a priori gamma expendido.
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 de la densidad de probabilidad mediante desarrollos de Neumann.
Se definen en este trabajo r-desarrollos de Neumann y se prueba que toda densidad de probabilidad f admite un desarrollo r-convergente a f.Los resultados obtenidos se aplican a la estimación de f sin la suposición de que sea de cuadrado integrable, estudiándose propiedades asintóticas de los estimadores e ilustrándose con un ejemplo de aplicación.
Estimación de la función cuantil asociada a una cópula C(x, y) mediante la función cuantil empírica.