Estimating median and other quantiles in nonparametric models

Ryszard Zieliński

The search session has expired. Please query the service again.

Displaying similar documents to “Estimating median and other quantiles in nonparametric models”

Variance of estimator of a discrete parameter

Antonín Lukš, Stanislav Komenda (1980)

Kybernetika

Similarity:

Unbiased estimators of multivariate discrete distributions and chi-square goodness-of-fit test.

Mikhail S. Nikulin, Vassiliy G. Voinov (1993)

Qüestiió

Similarity:

We consider the problem of estimation of the value of a real-valued function u(θ), θ = (θ, ..., θ), 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...

Theory of parameter estimation

Ryszard Zieliński (1997)

Banach Center Publications

Similarity:

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...

Finite sample optimality of extremes and mid-range

Chris A. J. Klaassen (1995)

Kybernetika

Similarity:

Estimating quantiles with Linex loss function. Applications to VaR estimation

Ryszard Zieliński (2005)

Applicationes Mathematicae

Similarity:

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...

A review of the results on the Stein approach for estimators improvement.

Vassiliy G. Voinov, Mikhail S. Nikulin (1995)

Qüestiió

Similarity:

Since 1956, a large number of papers have been devoted to Stein's technique of obtaining improved estimators of parameters, for several statistical models. We give a brief review of these papers, emphasizing those aspects which are interesting from the point of view of the theory of unbiased estimation.

Improving small area estimation by combining surveys: new perspectives in regional statistics.

Alex Costa, Albert Satorra, Eva Ventura (2006)

SORT

Similarity:

A national survey designed for estimating a specific population quantity is sometimes used for estimation of this quantity also for a small area, such as a province. Budget constraints do not allow a greater sample size for the small area, and so other means of improving estimation have to be devised. We investigate such methods and assess them by a Monte Carlo study. We explore how a complementary survey can be exploited in small area estimation. We use the context of the Spanish Labour...

On the performance of small-area estimators: fixed vs. random area parameters.

Alex Costa, Albert Satorra, Eva Ventura (2009)

SORT

Similarity: