Results 21 to 30 of about 18,318 (97)
NPCirc: An R Package for Nonparametric Circular Methods
Journal of Statistical Software, 2014 Nonparametric density and regression estimation methods for circular data are included in the R package NPCirc. Specifically, a circular kernel density estimation procedure is provided, jointly with different alternatives for choosing the smoothing ...
María Oliveira +2 more
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Improving for Network Traffic Bayes Classification Method Based on Correlation Information [PDF]
Jisuanji gongcheng, 2016 With the rapid growth of network applications,the efficiency of traditional network traffic classification method based on ports and payloads is reduced greatly.Meanwhile,most traffic flow classification methods do not consider the correlation among the ...
ZHAO Ying,TAN Yang
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Research of comparative analysis of nonparametric density estimation by applying Monte Carlo method
Lietuvos Matematikos Rinkinys, 2013 This paper presents nonparametric statistical estimation of distribution density. The Monte Carlo method is used to show the effects of kernel function for multimodal kernel density estimation.
Indrė Drulytė, Tomas Ruzgas
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Nonparametric Mean Estimation for Big-but-Biased Data
Proceedings, 2018 Some authors have recently warned about the risks of the sentence with enough data, the numbers speak for themselves. The problem of nonparametric statistical inference in big data under the presence of sampling bias is considered in this work.
Laura Borrajo, Ricardo Cao
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Nonparametric Multivariate Density Estimation: Case Study of Cauchy Mixture Model
Mathematics, 2021 Estimation of probability density functions (pdf) is considered an essential part of statistical modelling. Heteroskedasticity and outliers are the problems that make data analysis harder. The Cauchy mixture model helps us to cover both of them.
Tomas Ruzgas +2 more
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Clustering via Nonparametric Density Estimation: The R Package pdfCluster
Journal of Statistical Software, 2014 The R package pdfCluster performs cluster analysis based on a nonparametric estimate of the density of the observed variables. Functions are provided to encompass the whole process of clustering, from kernel density estimation, to clustering itself and ...
Adelchi Azzalini, Giovanna Menardi
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Nonparametric Copula Density Estimation Methodologies
MathematicsThis paper proposes several methodologies whose objective consists of securing copula density estimates. More specifically, this aim will be achieved by differentiating bivariate least-squares polynomials fitted to Deheuvels’ empirical copulas, by making
Serge B. Provost, Yishan Zang
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Mathematics, 2022 Nonparametric estimation for a probability density function that describes multivariate data has typically been addressed by kernel density estimation (KDE).
Jenny Farmer +2 more
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Radar Target Recognition Based on Semiparametric Density Estimation of SLC
Leida xuebao, 2012 In order to solve the problem of the decline of accuracy when using the nonparametric method—Stochastic Learning of the Cumulative (SLC) to estimate the density of High-Resolution Range Profile (HRRP) in radar target recognition under the condition that ...
Cui Shan-shan +2 more
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Journal of Statistical Software, 2014 Convex optimization now plays an essential role in many facets of statistics. We briefly survey some recent developments and describe some implementations of these methods in R .
Roger Koenker, Ivan Mizera
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