Results 71 to 80 of about 258,234 (187)
On the Way to Recovery: A Nonparametric Bias Free Estimation of Recovery Rate Densities [PDF]
In this paper we analyse recovery rates on defaulted bonds using the Standard and Poor’s/PMD database for the years 1981-1999. Due to the specific nature of the data (observations lie within 0 and 1), we must rely on nonstandard econometric techniques ...
Olivier RENAULT, Olivier SCAILLET
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Weakly supervised segment annotation via expectation kernel density estimation
IET Computer Vision, 2019 Since the labelling for the positive images/videos is ambiguous in weakly supervised segment annotation, negative mining‐based methods that only use the intra‐class information emerge. In these methods, negative instances are utilised to penalise unknown
Liantao Wang, Qingwu Li, Jianfeng Lu
doaj +1 more source
ROBUST KERNEL ESTIMATOR FOR DENSITIES OF UNKNOWN [PDF]
Results on nonparametric kernel estimators of density differ according to the assumed degree of density smoothness; it is often assumed that the density function is at least twice differentiable.
Victoria Zinde-Walsh, Yulia Kotlyarova
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Nonparametric Density Estimation for Positive Time Series [PDF]
The Gaussian kernel density estimator is known to have substantial problems for bounded random variables with high density at the boundaries. For i.i.d. data several solutions have been put forward to solve this boundary problem. In this paper we propose
Jeroen V.K. Rombouts, Taoufik Bouezmarni
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, 2018 In this article we perform an asymptotic analysis of Bayesian parallel density estimators which are based on logspline density estimation. The parallel estimator we introduce is in the spirit of a kernel density estimator introduced in recent studies. We
Conlon, Erin +2 more
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Kernel Density Estimation in the Study of Star Clusters
Open Astronomy, 2016 The kernel estimator method is used to evaluate the surface and spatial star number density in star clusters. Both density maps and radial density profiles are plotted.
Seleznev Anton F.
doaj +1 more source
Adaptive Clustering Using Kernel Density Estimators
, 2017 We derive and analyze a generic, recursive algorithm for estimating all splits in a finite cluster tree as well as the corresponding clusters. We further investigate statistical properties of this generic clustering algorithm when it receives level set estimates from a kernel density estimator.
Steinwart, Ingo +2 more
openaire +3 more sources
Ultrasound Entropy Imaging Based on the Kernel Density Estimation: A New Approach to Hepatic Steatosis Characterization. [PDF]
Diagnostics (Basel), 2023 Gao R +5 more
europepmc +1 more source
Kernel density estimation on the Siegel space applied to radar processing
, 2016 Main techniques of probability density estimation on Riemannian manifolds are reviewed in the case of the Siegel space. For computational reasons we chose to focus on the kernel density estimation.
Angulo, Jesus +2 more
core +1 more source
Bandwidth Selection for Semiparametric Estimators Using the m-out-of-n Bootstrap [PDF]
This paper considers a class of semiparametric estimators that take the form of density-weighted averages. These arise naturally in a consideration of semiparametric methods for the estimation of index and sample-selection models involving preliminary ...
Chuan Goh
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