Displaying similar documents to “Properly recorded estimate and confidence regions obtained by an approximate covariance operator in a special nonlinear model”

Linear versus quadratic estimators in linearized models

Lubomír Kubáček (2004)

Applications of Mathematics

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In nonlinear regression models an approximate value of an unknown parameter is frequently at our disposal. Then the linearization of the model is used and a linear estimate of the parameter can be calculated. Some criteria how to recognize whether a linearization is possible are developed. In the case that they are not satisfied, it is necessary to take into account either some quadratic corrections or to use the nonlinear least squares method. The aim of the paper is to find some criteria...

Estimates of reliability for the normal distribution

Jan Hurt (1980)

Aplikace matematiky

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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.

Optimal estimator of hypothesis probability for data mining problems with small samples

Andrzej Piegat, Marek Landowski (2012)

International Journal of Applied Mathematics and Computer Science

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The paper presents a new (to the best of the authors' knowledge) estimator of probability called the "Epₕ√2 completeness estimator" along with a theoretical derivation of its optimality. The estimator is especially suitable for a small number of sample items, which is the feature of many real problems characterized by data insufficiency. The control parameter of the estimator is not assumed in an a priori, subjective way, but was determined on the basis of an optimization criterion (the...