Results 221 to 230 of about 81,542 (267)
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Robust kernels for kernel density estimation
Economics Letters, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wang, Shaoping +3 more
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On Convergence of Kernel Learning Estimators
SIAM Journal on Optimization, 2010The paper studies convex stochastic optimization problems in a reproducing kernel Hilbert space (RKHS). The objective (risk) functional depends on functions from this RKHS and takes the form of a mathematical expectation (integral) of a nonnegative integrand (loss function) over a probability measure.
Vladimir I. Norkin, Michiel A. Keyzer
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Estimating the Variance of a Kernel Density Estimation
2010This 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 +2 more
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Bootstrapping kernel spectral density estimates with kernel bandwidth estimation
2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., 2004We address the problem of confidence interval estimation of spectral densities using the bootstrap. Of special interest is the choice of the kernel global bandwidth. First, we investigate resampling based techniques for the choice of the bandwidth.
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A Note on the Variable Kernel Estimate
Biometrical Journal, 1982AbstractBy a simple example it is shown how in special cases the variable kernel estimate may not give the correct qualitative impression of the estimated density.To exclude such effects a slightly modified definition of the bandwidth of the kernels is proposed.
Schäfer, H., Trampisch, H. J.
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Undersmoothed Kernel Entropy Estimators
IEEE Transactions on Information Theory, 2008We develop a ldquoplug-inrdquo kernel estimator for the differential entropy that is consistent even if the kernel width tends to zero as quickly as 1/N, where N is the number of independent and identically distributed (i.i.d.) samples. Thus, accurate density estimates are not required for accurate kernel entropy estimates; in fact, it is a good idea ...
Liam Paninski, Masanao Yajima
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Kernel Estimates of Dose Response
Biometrics, 1988A nonparametric method for analyzing quantal response data from an indirect bioassay experiment is proposed. Kernel estimates of the dose-response curve are used to develop approximate confidence intervals for (i) the optimal combination dose of a drug with therapeutic effects at low doses and toxic effects at high doses, and (ii) the lethal dose ...
J G, Staniswalis, V, Cooper
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Kernel Estimation of a Characteristic Function
Journal of Mathematical Sciences, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Abdushukurov, A. A., Norboev, F. Sh.
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Reweighted kernel density estimation
Computational Statistics & Data Analysis, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Martin L. Hazelton, Berwin A. Turlach
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Complementary Kernel Density Estimation
Pattern Recognition Letters, 2012Generative models for vision and pattern recognition have been overshadowed in recent years by powerful non-parametric discriminative models. These discriminative models can learn arbitrary decision boundaries between classes and have proved very effective in classification and detection problems.
Xu Miao, Ali Rahimi, Rajesh P. N. Rao
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