Estimating L-functionals for heavy-tailed distributions and application.
Estimating Matrices.
Estimating median and other quantiles in nonparametric models
Though widely accepted, in nonparametric models admitting asymmetric distributions the sample median, if n=2k, may be a poor estimator of the population median. Shortcomings of estimators which are not equivariant are presented.
Estimating normal density and normal distribution function: is Kolmogorov's estimator admissible?
The statistical estimation problem of the normal distribution function and of the density at a point is considered. The traditional unbiased estimators are shown to have Bayes nature and admissibility of related generalized Bayes procedures is proved. Also inadmissibility of the unbiased density estimator is demonstrated.
Estimating Parameters of a Multiplicative Seasonal ARIMA Model Using Prediction Error Method Algorithm
Estimating quantiles with Linex loss function. Applications to VaR estimation
Sometimes, e.g. in the context of estimating VaR (Value at Risk), underestimating a quantile is less desirable than overestimating it, which suggests measuring the error of estimation by an asymmetric loss function. As a loss function when estimating a parameter θ by an estimator T we take the well known Linex function exp{α(T-θ)} - α(T-θ) - 1. To estimate the quantile of order q ∈ (0,1) of a normal distribution N(μ,σ), we construct an optimal estimator in the class of all estimators of the form...
Estimating Regression Coefficients from Survey Data by Asymptotic Desingn-Cum-Model Based Approach.
Estimating Survivor Function Using Optimally Selected Order Statistics.
Estimating the angles of arrival of multiple plane waves. The statistical performance of the music and the minimum norm algorithms
Estimating the conditional expectations for continuous time stationary processes
One of the basic estimation problems for continuous time stationary processes , is that of estimating based on the observation of the single block when the actual distribution of the process is not known. We will give fairly optimal universal estimates of this type that correspond to the optimal results in the case of discrete time processes.
Estimating the conditional tail expectation in the case of heavy-tailed losses.
Estimating the contamination level of data in the framework of linear regression analysis.
An estimator of the contamination level of data is proposed in the framework of linear models and its asymptotic behavior is investigated. A numerical study illustrates its finite sample performance under an alternative.
Estimating the dimension of a linear model
Estimating the fuzzy inequality associated with a fuzzy random variable in random samplings from finite populations
In a recent paper we have introduced the fuzzy hyperbolic inequality index, to quantify the inequality associated with a fuzzy random variable in a finite population. In previous papers, we have also proven that the classical hyperbolic inequality index associated with real-valued random variables in finite populations can be unbiasedly estimated in random samplings. The aim of this paper is to analyze the problem of estimating the population fuzzy hyperbolic index associated with a fuzzy random...
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...
Estimating the Variance of a Finite Population under a Superpopulation Model.
Estimating the Variance of the Ratio Estimator for the Midzuno-Sen Sampling Scheme.
Estimating unemployment in very small areas.
Estimation and annealing for Gibbsian fields
Estimation and bimodality testing in the cusp model
The probability density function of the stochastic cusp model belongs to the class of generalized exponential distributions. It accommodates variable skewness, kurtosis, and bimodality. A statistical test for bimodality of the stochastic cusp model using the maximum likelihood estimation and delta method for Cardan's discriminant is introduced in this paper, as is a necessary condition for bimodality, which can be used for simplified testing to reject bimodality. Numerical maximum likelihood estimation...