Results 261 to 270 of about 4,333,581 (301)

A Novel Ultra-High Voltage Direct Current Line Fault Diagnosis Method Based on Principal Component Analysis and Kernel Density Estimation. [PDF]

Sensors (Basel)
Zhang H, Gong Q.
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Asynchronous calibration of a CT scanner for bone mineral density estimation: sources of error and correction. [PDF]

JBMR Plus
Dudle A, Ith M, Egli R, Heverhagen J, Gugler Y, Wapp C, Frauchiger DA, Lippuner K, Jackowski C, Zysset P.   +9 more
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An Evaluation of Multi-Channel Sensors and Density Estimation Learning for Detecting Fire Blight Disease in Pear Orchards. [PDF]

Sensors (Basel)
Veres M, Tarry C, Grigg-McGuffin K, McFadden-Smith W, Moussa M.   +4 more
europepmc   +1 more source

Erratum: Volumetric Breast Density Estimation From Three-Dimensional Reconstructed Digital Breast Tomosynthesis Images Using Deep Learning. [PDF]

JCO Clin Cancer Inform
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Correction of Density Estimators that are not Densities

Scandinavian Journal of Statistics, 2003
Abstract. Several old and new density estimators may have good theoretical performance, but are hampered by not being bona fide densities; they may be negative in certain regions or may not integrate to 1. One can therefore not simulate from them, for example.
Glad, Ingrid K., Hjort, Nils Lid, Ushakov, Nikolai G.   +2 more
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Adaptive density estimation

2006
This demonstration illustrates the APDF tree: an adaptive tree that supports the effective and effcient computation of continuous density information. The APDF tree allocates more partition points in non-linear areas of the density function and fewer points in linear areas of the density function.
Mazeika, Arturas, Böhlen, Michael H, Taliun, Andrej   +2 more
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On parametric density estimation

Biometrika, 1989
Let p(x,\(\vartheta)\) be the density of a random variable x. A random sample \(s_ n=(x_ 1,...,x_ n)\) of size n is available from the distribution. By y a future observation from this distribution is denoted. Two distinct methods of estimating p(y\(| \vartheta)\) are known. The estimative method uses \[ p(y| {\hat \vartheta}_ n)=p(y| \vartheta ={\hat \
El-Sayyad, G. M., Samiuddin, M., Al-Harbey, A. A.   +2 more
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Estimation of Functionals of a Density

Theory of Probability & Its Applications, 1993
See the review in Zbl 0762.62012.
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SUBSAMPLING FOR DENSITY ESTIMATION

Statistics & Risk Modeling, 2002
Summary: We consider nonparametric density estimation from the point of view of coverage probability. To take into account the problem of bias in bootstrapping nonparametric density kernel estimators, \textit{P. Hall} [Statistics 22, No. 2, 215-232 (1991; Zbl 0809.62031); Ann. Stat. 20, No. 2, 675-694 (1992; Zbl 0748.62028)] showed that it is better to
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Estimating the Variance of a Kernel Density Estimation

2010
This article proposes an interval-valued extension of kernel density estimation. We show that the imprecision of this interval-valued estimation is highly correlated with the variance of the density estimation induced by the statistical variations of the set of observations.
Bilal Nehme, Olivier Strauss, Kevin Loquin   +2 more
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