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Implementation of the MR tractography visualization kit based on the anisotropic Allen-Cahn equation

Pavel Strachota (2009)

Kybernetika

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...

Improving both domain and total area estimation by composition.

Alex Costa, Albert Satorra, Eva Ventura (2004)

SORT

In this article we propose small area estimators for both the small and large area parameters. When the objective is to estimate parameters at both levels, optimality is achieved by a sample design that combines fixed and proportional allocation. In such a design, one fraction of the sample is distributed proportionally among the small areas and the rest is evenly distributed. Simulation is used to assess the performance of the direct estimator and two composite small area estimators, for a range...

Improving feature selection process resistance to failures caused by curse-of-dimensionality effects

Petr Somol, Jiří Grim, Jana Novovičová, Pavel Pudil (2011)

Kybernetika

The purpose of feature selection in machine learning is at least two-fold - saving measurement acquisition costs and reducing the negative effects of the curse of dimensionality with the aim to improve the accuracy of the models and the classification rate of classifiers with respect to previously unknown data. Yet it has been shown recently that the process of feature selection itself can be negatively affected by the very same curse of dimensionality - feature selection methods may easily over-fit...

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

Alex Costa, Albert Satorra, Eva Ventura (2006)

SORT

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 Force Survey...

Incorporating patients' characteristics in cost-effectiveness studies with clinical trial data: a flexible Bayesian approach.

Francisco José Vázquez Polo, Miguel Angel Negrín Hernández (2004)

SORT

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,...

Independencia entre las cuestiones en el análisis factorial de tablas disyuntivas incompletas con preguntas condicionadas.

Amaya Zárraga, Beatriz Goitisolo (1999)

Qüestiió

El análisis de correspondencias múltiples (ACM) estudia la relación entre varias variables cualitativas definidas sobre una misma población. Sin embargo, una de las principales fuentes de información son las encuestas donde es frecuente encontrar cierto número de datos ausentes y de preguntas condicionadas. Escofier (Escofier 1981) propone analizar la tabla disyuntiva incompleta sustituyendo la marginal real de la tabla sobre los individuos por una marginal impuesta constante. El análisis de la...

Influence diagnostics in exponentiated-Weibull regression models with censored data.

Edwin M. M. Ortega, Vicente G. Cancho, Heleno Bolfarine (2006)

SORT

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from the error assumptions and the presence of outliers and influential observations with the fitted models. The literature provides plenty of approaches for detecting outlying or influential observations in data sets. In this paper, we follow the local influence approach (Cook 1986) in detecting influential observations with exponentiated-Weibull regression models. The relevance of the...

Insensitivity region for variance components in general linear model

Hana Boháčová (2008)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

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.

Interpretation and optimization of the k -means algorithm

Kristian Sabo, Rudolf Scitovski (2014)

Applications of Mathematics

The paper gives a new interpretation and a possible optimization of the well-known k -means algorithm for searching for a locally optimal partition of the set 𝒜 = { a i n : i = 1 , , m } which consists of k disjoint nonempty subsets π 1 , , π k , 1 k m . For this purpose, a new divided k -means algorithm was constructed as a limit case of the known smoothed k -means algorithm. It is shown that the algorithm constructed in this way coincides with the k -means algorithm if during the iterative procedure no data points appear in the Voronoi diagram....

Interpretation of pattern classification results, obtained from a test set

Edgard Nyssen (1998)

Kybernetika

The present paper presents and discusses a methodology for interpreting the results, obtained from the application of a pattern classifier to an independent test set. It addresses the problem of testing the random classification null hypothesis in the multiclass case, by introducing an exact probability technique. The discussion of this technique includes the presentation of an interval estimation technique for the probability of correct classification, which is slightly more accurate than the ones...

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