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New type of gamma kernel density estimator
Journal of the Korean Statistical Society, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yoshihiko Maesono
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A gamma kernel density estimation for insurance loss data
Insurance: Mathematics and Economics, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Joseph H T Kim, Yongho Jeon
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Predicting visual attention using gamma kernels
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016Saliency measures are a popular way to predict visual attention. However, saliency is normally tested on sets of single resolution images that are unlike what the human vision system sees. We propose a new saliency measure based on convolving images with 2D gamma kernels which function as a comparison between a center and a surrounding neighborhood ...
Ryan Burt +4 more
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Asymptotic results in gamma kernel regression
Communications in Statistics - Theory and Methods, 2015AbstractBased on the Gamma kernel density estimation procedure, this article constructs a nonparametric kernel estimate for the regression functions when the covariate are nonnegative. Asymptotic normality and uniform almost sure convergence results for the new estimator are systematically studied, and the finite performance of the proposed estimate is
Jianhong Shi, Weixing Song
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Family of the generalised gamma kernels: a generator of asymmetric kernels for nonnegative data
Journal of Nonparametric Statistics, 2015Unlike symmetric kernels, so far exploring asymptotics on asymmetric kernels has relied on diversified approaches. This paper proposes a family of the generalised gamma (GG) kernels that is built on the probability density function of the GG distribution [Stacy, E.W.
Masayuki Hirukawa, Mari Sakudo
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Fast modeling of gamma-gamma density measurementsvia gamma-ray point-kernel approximations
Geophysics, 2019ABSTRACT Forward-modeling algorithms based on flux sensitivity functions are commonly recognized as fast, reliable, and the most efficient way to implement inversion-based interpretation algorithms for borehole nuclear measurements. Second-order sensitivity functions enhance the accuracy of fast-forward-modeling algorithms in complex ...
Mathilde Luycx, Carlos Torres-Verdín
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On Lévy Semistationary Processes with a Gamma Kernel
2015This paper studies some probabilistic properties of a Levy semistationary process when the kernel is given by \(\varphi _{\alpha,\lambda }\left (s\right ) = e^{-\lambda s}s^{\alpha }\) for α > −1 and λ > 0. We study the stationary distribution induced by this process.
Pedersen, Jan, Sauri, Orimar
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Modules whose surjective endomorphisms have a \(\gamma\)-small kernels
2022Summary: In this paper, we introduce a proper generalization of that of Hopfian modules, called \(\gamma\)-Hopfian modules. A right \(R\)-module \(M\) is said to be \(\gamma\)-Hopfian, if any surjective endomorphism of \(M\) has a \(\gamma\)-small kernel. Some basic characterizations of \(\gamma\)-Hopfian modules are proved.
El Moussaouy, Abderrahim +1 more
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Optimized Derivative Kernels for Gamma Ray Spectroscopy
AIP Conference Proceedings, 2007In gamma ray spectroscopy, the photon detectors measure the number of photons with energy that lies in an interval which is called a channel. This accumulation of counts produce a measuring function that its deviation from the ideal one may produce high noise in the unfolded spectrum.
D. S. Vlachos +4 more
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Artificial neural networks with gamma kernels for automatic target detection
Proceedings of International Conference on Neural Networks (ICNN'96), 2002The quadratic gamma detector (QGD) has been used successfully to discriminate man made objects from background clutter in synthetic aperture (SAR) radar imagery. It implements a linear discriminant function based on quadratic terms of the image intensity of a pixel under observation and of its surroundings.
Munchurl Kim, José C. Príncipe
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