Identification with interruptions as an anti-bursting device
IFS approximations of distribution functions and related optimization problems.
Implementation of the MR tractography visualization kit based on the anisotropic Allen-Cahn equation
Magnetic Resonance Diffusion Tensor Imaging (MR–DTI) is a noninvasive in vivo method capable of examining the structure of human brain, providing information about the position and orientation of the neural tracts. After a short introduction to the principles of MR–DTI, this paper describes the steps of the proposed neural tract visualization technique based on the DTI data. The cornerstone of the algorithm is a texture diffusion procedure modeled mathematically by the problem for the Allen–Cahn...
Improvement of Fisher's test of periodicity
Fisher's test of periodicity in time series and Siegel's version of this test for compound periodicities are investigated in the paper. An improvement increasing the power of the test is suggested and demonstrated by means of numerical simulations.
Improving on Two-Stage Estimators for Scale Families.
In Information Theoretic Argument for the Validity of the Exponential Model.
Incorporating patients' characteristics in cost-effectiveness studies with clinical trial data: a flexible Bayesian approach.
Most published research on the comparison between medical treatment options merely compares the results (effectiveness and cost) obtained for each treatment group. The present work proposes the incorporation of other patient characteristics into the analysis. Most of the studies carried out in this context assume normality of both costs and effectiveness. In practice, however, the data are not always distributed according to this assumption. Alternative models have to be developed.In this paper,...
Inequalities between hypergeometric tails.
Inference in linear models with inequality constrained parameters
In many econometric applications there is prior information available for some or all parameters of the underlying model which can be formulated in form of inequality constraints. Procedures which incorporate this prior information promise to lead to improved inference. However careful application seems to be necessary. In this paper we will review some methods proposed in the literature. Among these there are inequality constrained least squares (ICLS), constrained maximum likelihood (CML) and...
Inference on overlap coefficients under the Weibull distribution : equal shape parameter
In this paper we consider three measures of overlap, namely Matusia’s measure , Morisita’s measure and Weitzman’s measure . These measures are usually used in quantitative ecology and stress-strength models of reliability analysis. Herein we consider two Weibull distributions having the same shape parameter and different scale parameters. This distribution is known to be the most flexible life distribution model with two parameters. Monte Carlo evaluations are used to study the bias and precision...
Inference on overlap coefficients under the Weibull distribution: Equal shape parameter
In this paper we consider three measures of overlap, namely Matusia's measure ρ, Morisita's measure λ and Weitzman's measure Δ. These measures are usually used in quantitative ecology and stress-strength models of reliability analysis. Herein we consider two Weibull distributions having the same shape parameter and different scale parameters. This distribution is known to be the most flexible life distribution model with two parameters. Monte Carlo evaluations are used to study the bias and precision...
Inference on the location parameter of exponential populations
Studentization and analysis of variance are simple in Gaussian families because X̅ and S² are independent random variables. We exploit the independence of the spacings in exponential populations with location λ and scale δ to develop simple ways of dealing with inference on the location parameter, namely by developing an analysis of scale in the homocedastic independent k-sample problem.
Inferencia bayesiana en mixturas: métodos aproximados.
The problem of approximating mixtures of distributions has received considerable attention recently. In this paper we consider problems of estimating the mixing proportions of a finite mixture from a Bayesian perspective. The problems which arise from this methodology are basically approximations of finite measures of distributions. We propose two approximating methods and prove that under certain conditions both methods are asymptotically equivalent to a third method, which turns out to be simpler...
Inferencia bayesiana sobre el coeficiente de correlación de una población normal bivariante.
En el presente artículo se utiliza el método de maximización de la información desconocida para deducir las distribuciones inicial y final de referencia cuando se trata de hacer inferencias sobre el coeficiente de correlación de una población normal bivariante.
Inferential procedures on a generalized Rayleigh variate. I
Inferential procedures on a generalized Rayleigh variate. II
Influence of contamination level deviations on the test error probabilities
Information inequalities for the minimax risk of sequential estimators (with applications)
Information inequalities for the minimax risk of sequential estimators are derived in the case where the loss is measured by the squared error of estimation plus a linear functional of the number of observations. The results are applied to construct minimax sequential estimators of: the failure rate in an exponential model with censored data, the expected proportion of uncensored observations in the proportional hazards model, the odds ratio in a binomial distribution and the expectation of exponential...
Insensitivity region for variance components in general linear model
In linear regression models the estimator of variance components needs a suitable choice of a starting point for an iterative procedure for a determination of the estimate. The aim of this paper is to find a criterion for a decision whether a linear regression model enables to determine the estimate reasonably and whether it is possible to do so when using the given data.
Instrumental weighted variables under heteroscedasticity. Part I – Consistency
The proof of consistency instrumental weighted variables, the robust version of the classical instrumental variables is given. It is proved that all solutions of the corresponding normal equations are contained, with high probability, in a ball, the radius of which can be selected - asymptotically - arbitrarily small. Then also -consistency is proved. An extended numerical study (the Part II of the paper) offers a picture of behavior of the estimator for finite samples under various types and levels...