The most stable estimator of location under integrable contaminants
If a symmetric distribution is ε-contaminated and the contaminants have finite first moments, the median may cease to be the most robust estimator of location.
The mutual information estimation in the sampling with replacement
The stability of the problem of statistical estimation and choice of the loss function
The UMVUE of P(X<Y) Based on Type-II Censored Samples from Weinman Multivariate Exponential Distributions.
Theory of parameter estimation
0. Introduction and summary. The analysis of data from the gravitational-wave detectors that are currently under construction in several countries will be a challenging problem. The reason is that gravitational-vawe signals are expected to be extremely weak and often very rare. Therefore it will be of great importance to implement optimal statistical methods to extract all possible information about the signals from the noisy data sets. Careful statistical analysis based on correct application of...
Three-Stage Estimation Procedures for the Negative Exponential Distributions.
Trimmed Estimators in Regression Framework
From the practical point of view the regression analysis and its Least Squares method is clearly one of the most used techniques of statistics. Unfortunately, if there is some problem present in the data (for example contamination), classical methods are not longer suitable. A lot of methods have been proposed to overcome these problematic situations. In this contribution we focus on special kind of methods based on trimming. There exist several approaches which use trimming off part of the observations,...
Two problems of minimax estimation
Two stage linear model with constraints
Über ein nichtparametrisches Schätzproblem.
Unbiased estimation for two-parameter exponential distribution under time censored sampling
The problem considered is that of unbiased estimation for a two-parameter exponential distribution under time censored sampling. We obtain a necessary form of an unbiasedly estimable parametric function and prove that there does not exist any unbiased estimator of the parameters and the mean of the distribution. For reliability estimation at a specified time point, we give a necessary and sufficient condition for the existence of an unbiased estimator and suggest an unbiased estimator based on a...
Unbiased estimation of reliability for two-parameter exponential distribution under time censored sampling
The problem considered is that of unbiased estimation of reliability for a two-parameter exponential distribution under time censored sampling. We give necessary and sufficient conditions for the existence of uniformly minimum variance unbiased estimator and also provide a characterization of a complete class of unbiased estimators in situations where unbiased estimators exist.
Unbiased estimators of multivariate discrete distributions and chi-square goodness-of-fit test.
We consider the problem of estimation of the value of a real-valued function u(θ), θ = (θ1, ..., θk)T, on the basis of a sample from non-truncated or truncated multivariate Modified Power Series Distributions. Using the general theory of estimation and the results of Patil (1965) and Patel (1978) we give the tables of MVUE's for functions of parameter θ of trinomial, multinomial, negative-multinomial and left-truncated modified power series distributions. We have applied the properties of MVUE's...
Uncertainty of coordinates and looking for dispersion of GPS receiver
The aim of the paper is to show some possible statistical solution of the estimation of the dispersion of the GPS receiver. The presented method (based on theory of linear model with additional constraints of type I) can serve for an improvement of the accuracy of estimators of coordinates acquired from the GPS receiver.
Underparametrization of weakly nonlinear regression models
A large number of parameters in regression models can be serious obstacle for processing and interpretation of experimental data. One way how to overcome it is an elimination of some parameters. In some cases it need not deteriorate statistical properties of estimators of useful parameters and can help to interpret them. The problem is to find conditions which enable us to decide whether such favourable situation occurs.
Ungünstige Verteilungen bei einparametrigen Parameterschätzproblemen.
Uniform Minimum Variance Unbiased Estimators for Bivariate Families.
Uniformly best linear-quadratic estimator in a special structure of the regression model.
Uso del estadístico Dn de Kolmogorov-Smirnov en inferencia paramétrica.
Se estudia un método de estimación paramétrica basado en la minimización del estadístico Dn de Kolmogorov-Smirnov. Se prueba la existencia y unicidad de este estimador en familias de distribuciones monótonas en alguno de sus parámetros y se compara computacionalmente con el método de máxima verosimilitud.
Variance components and an additional experiment
Estimators of parameters of an investigated object can be considered after some time as insufficiently precise. Therefore, an additional measurement must be realized. A model of a measurement, taking into account both the original results and the new ones, has a litle more complicated covariance matrix, since the variance components occur in it. How to deal with them is the aim of the paper.