Error analysis of a pairwise summation algorithm to compute the sample variance.
Error Bounds for Rank 1 Lattice Quadrature Rules Modulo Composites.
Error estimation and optimization of the functional algorithms of a random walk on a grid which are applied to solving the Dirichlet problem for the Helmholtz equation.
Estabilización de la varianza de una distribución hipergeométrica.
En este trabajo se determina una transformación tipo arco seno para una distribución hipergeométrica H(N,D = pN,n) de forma que estabilice la varianza de la misma en función de la fracción p de objetos de un cierto tipo. Como caso particular de las expresiones obtenidas se deducen las dadas por F. J. Anscombe (1948) para la distribución binomial B(n,p). Al final del trabajo se efectúa una investigación numérica de los resultados obtenidos y se dan algunas aplicaciones para realizar inferencias sobre...
Estimates of reliability for the normal distribution
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.
Estimating a resource selection function with line transect sampling.
Estimating from cross-sectional categorical data subject to misclassification and double sampling: moment-based, maximum likelihood and quasi-likelihood approaches.
Estimating the dimension of a linear model
Estimating the shape parameter of the Topp-Leone distribution based on Type I censored samples
The shape parameter of the Topp-Leone distribution is estimated from classical and Bayesian points of view based on Type I censored samples. The maximum likelihood and the approximate maximum likelihood estimates are derived. The Bayes estimate and the associated credible interval are approximated by using Lindley's approximation and Markov Chain Monte Carlo using the importance sampling technique. Monte Carlo simulations are performed to compare the performances of the proposed methods. Real and...
Estimation automatique de la densité
Estimation in connecting measurements with constraints of type II
This paper is a continuation of the paper [6]. It dealt with parameter estimation in connecting two–stage measurements with constraints of type I. Unlike the paper [6], the current paper is concerned with a model with additional constraints of type II binding parameters of both stages. The article is devoted primarily to the computational aspects of algorithms published in [5] and its aim is to show the power of -optimum estimators. The aim of the paper is to contribute to a numerical solution...
Estimation non paramétrique du -quantile conditionnel et ses dérivées partielles
Estimation non-paramétrique par noyaux : régression polynomiale mobile
Estimation of anisotropic gaussian fields through Radon transform
We estimate the anisotropic index of an anisotropic fractional brownian field. For all directions, we give a convergent estimator of the value of the anisotropic index in this direction, based on generalized quadratic variations. We also prove a central limit theorem. First we present a result of identification that relies on the asymptotic behavior of the spectral density of a process. Then, we define Radon transforms of the anisotropic fractional brownian field and prove that these processes admit...
Estimation of anisotropic Gaussian fields through Radon transform
We estimate the anisotropic index of an anisotropic fractional Brownian field. For all directions, we give a convergent estimator of the value of the anisotropic index in this direction, based on generalized quadratic variations. We also prove a central limit theorem. First we present a result of identification that relies on the asymptotic behavior of the spectral density of a process. Then, we define Radon transforms of the anisotropic fractional Brownian field and prove that these processes...
Estimation of dispersion in nonlinear regression models with constraints
Dispersion of measurement results is an important parameter that enables us not only to characterize not only accuracy of measurement but enables us also to construct confidence regions and to test statistical hypotheses. In nonlinear regression model the estimator of dispersion is influenced by a curvature of the manifold of the mean value of the observation vector. The aim of the paper is to find the way how to determine a tolerable level of this curvature.
Estimation of simple linear regression model using ranked set sampling.
Estimation of the parameters of the reversed generalized logistic distribution with progressive censoring data.
Estimators of the asymptotic variance of stationary point processes - a comparison
We investigate estimators of the asymptotic variance of a –dimensional stationary point process which can be observed in convex and compact sampling window . Asymptotic variance of is defined by the asymptotic relation (as ) and its existence is guaranteed whenever the corresponding reduced covariance measure has finite total variation. The three estimators discussed in the paper are the kernel estimator, the estimator based on the second order intesity of the point process and the...
Estudio de algunas secuencias pseudoaleatorias de aplicación criptográfica.
Pseudorandom binary sequences are required in stream ciphers and other applications of modern communication systems. In the first case it is essential that the sequences be unpredictable. The linear complexity of a sequence is the amount of it required to define the remainder. This work addresses the problem of the analysis and computation of the linear complexity of certain pseudorandom binary sequences. Finally we conclude some characteristics of the nonlinear function that produces the sequences...