Results 21 to 30 of about 10,633,056 (308)
Theoretical and Empirical Differences between Diagonal and Full BEKK for Risk Management
Energies, 2018 The purpose of the paper is to explore the relative biases in the estimation of the Full BEKK model as compared with the Diagonal BEKK model, which is used as a theoretical and empirical benchmark.
David E. Allen, Michael McAleer
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Non-Parametric Clustering Using Deep Neural Networks
IEEE Access, 2020 In this paper, a novel algorithm for non-parametric image clustering, is proposed. Non-parametric clustering methods operate by considering the number of clusters unknown as opposed to parametric clustering, where the number of clusters is known a priori.
Christos Avgerinos +3 more
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The use of statistics in social sciences [PDF]
Journal of Humanities and Applied Social Sciences, 2019 Purpose – The purpose this paper is to review some of the statistical methods used in the field of social sciences. Design/methodology/approach – A review of some of the statistical methodologies used in areas like survey methodology, official statistics,
Petros Maravelakis
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Receiver Operator Characteristic Analysis of Biomarkers Evaluation in Diagnostic Research [PDF]
Journal of Clinical and Diagnostic Research, 2018 Receiver Operator Characteristic (ROC) analysis is the choice of method in evaluation of biomarkers in bioinformatics research. However, there is no single method and also no single accuracy index in evaluating diagnostic tools.
Karimollah Hajian-Tilaki
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Non-parametric contextual stochastic search
, 2016 Stochastic search algorithms are black-box optimizer of an objective function. They have recently gained a lot of attention in operations research, machine learning and policy search of robot motor skills due to their ease of use and their generality ...
Gerhard Neumann (17164168) +3 more
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Non-parametric random simulation results.
, 2022 Non-parametric random simulation results.
Liping Zhai (13844318) +3 more
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Non-parametric specification testing of non-nested econometric models [PDF]
, 1994 We consider the non-nested testing prqblem of non-parametric regressions. We show that, when the regression functions are unknown under both the null and the alternative hypotheses, an extension of the J-test procedure of Davidson and Mackinnon (1981 ...
Delgado, Miguel A. +2 more
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Adaptive weighted non-parametric background model for efficient video coding [PDF]
, 2017 Dynamic background frame based video coding using mixture of Gaussian (MoG) based background modelling has achieved better rate distortion performance compared to the H.264 standard.
Paul, Manoranjan +3 more
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Non-Parametric Function Fitting
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1972 Summary In this note we consider the problem of fitting a general functional relationship between two variables. We require only that the function to be fitted is, in some sense, “smooth”, and do not assume that it has a known mathematical form involving only a finite number of unknown parameters.
Priestley, M. B., Chao, M. T.
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Frontiers in Genetics, 2022 Most genomic prediction models are linear regression models that assume continuous and normally distributed phenotypes, but responses to diseases such as stripe rust (caused by Puccinia striiformis f. sp.
Lance F. Merrick +3 more
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