Results 11 to 20 of about 6,398 (252)
LogConcDEAD: An R Package for Maximum Likelihood Estimation of a Multivariate Log-Concave Density [PDF]
Journal of Statistical Software, 2008 In this article we introduce the R package LogConcDEAD (Log-concave density estimation in arbitrary dimensions). Its main function is to compute the nonparametric maximum likelihood estimator of a log-concave density.
Madeleine Cule +2 more
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Targeted decrease of portal hepatic pressure gradient improves ascites control after TIPS
Hepatology, EarlyView., 2022 The river diagram demonstrates that after transjugular intrahepatic portosystemic shunt insertion (TIPS) the majority of patients without ascites and 50% of the patients with ascites detectable at ultrasound, show the best response in the long term follow‐up.
Alexander Queck +14 more
wiley +1 more source
Nonparametric estimation of multivariate convex-transformed densities
The Annals of Statistics, 2010 Published in at http://dx.doi.org/10.1214/10-AOS840 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Seregin, Arseni, Wellner, Jon A.
openaire +5 more sources
Transformation-based nonparametric estimation of multivariate densities
Journal of Multivariate Analysis, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Meng-Shiuh Chang, Ximing Wu
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Scientific Reports, 2023 Multivariate control charts have been applied in many sectors. One of the sectors that employ this method is network intrusion detection. However, the issue arises when the conventional control chart faces difficulty monitoring the network-traffic data ...
Muhammad Ahsan +3 more
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A nonparametric model for quality control of database search results in shotgun proteomics
BMC Bioinformatics, 2008 Background Analysis of complex samples with tandem mass spectrometry (MS/MS) has become routine in proteomic research. However, validation of database search results creates a bottleneck in MS/MS data processing.
Zhu Yunping +5 more
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Nonparametric estimation of multivariate scale mixtures of uniform densities
Journal of Multivariate Analysis, 2012 39 pages, 4 ...
Marios G. Pavlides, Jon A. Wellner
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Approximate inference of the bandwidth in multivariate kernel density estimation [PDF]
, 2011 Kernel density estimation is a popular and widely used non-parametric method for data-driven density estimation. Its appeal lies in its simplicity and ease of implementation, as well as its strong asymptotic results regarding its convergence to the true ...
Sanguinetti, G. +3 more
core +1 more source
Kernel Density Estimation: Theory and Application in Discriminant Analysis
Austrian Journal of Statistics, 2016 Nowadays, one can find a huge set of methods to estimate the density function of a random variable nonparametrically. Since the first version of the most elementary nonparametric density estimator (the histogram) researchers produced a vast amount of ...
Thomas Ledl
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Conditional density estimation with class probability estimators [PDF]
, 2009 Many regression schemes deliver a point estimate only, but often it is useful or even essential to quantify the uncertainty inherent in a prediction. If a conditional density estimate is available, then prediction intervals can be derived from it.
Remco R. Bouckaert +3 more
core +1 more source