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Kernel density estimation
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31	A PROBABILISTIC METHOD TO CALCULATE VOLCANIC SUSCEPTIBILITY S. Bartolini (1), A. Cappello (2), J. Martí (1), R. Sobradelo (1,3), S. Barde-CabussonGroup of Volcanology, SIMGEO (UB-CSIC), Institute of Earth Scien Add to Reading List Source URL: www.vuelco.net Language: English - Date: 2013-03-22 11:21:44 Density estimation Analysis Mathematics Non-parametric statistics Gaussian function Kernel density estimation
32	Calibrated estimation of a nonparametric income distribution from a few percentiles Jing Dai Universit¨ at Kassel, Department of Economics, Nora-Platiel-Str. 5, DKassel, Add to Reading List Source URL: www.statistics.gov.hk Language: English - Date: 2013-08-22 04:39:11 Welfare economics Statistical inference Distribution of wealth Nonparametric regression Smoothing spline Gini coefficient Lorenz curve Kernel density estimation Smoothing Statistics Regression analysis Non-parametric statistics
33	Dual Kernel Density Estimation as a Method for Describing Spatio-Temporal Changes in the Upper Austrian Food Retailing Market Eva Maria Jansenberger and Petra Staufer-Steinnocher Department of Economic Geography & Geoinf Add to Reading List Source URL: itcnt05.itc.nl Language: English - Date: 2005-02-27 17:00:00 Density estimation Kernel CrimeStat KDE Linux kernel Normal distribution Bandwidth Market concentration Point pattern analysis Statistics Non-parametric statistics Kernel density estimation
34	arXiv:1202.0515v3 [stat.ML] 21 AugHigh-Dimensional Feature Selection by Feature-Wise Kernelized Lasso Makoto Yamada1 , Wittawat Jitkrittum2 , Leonid Sigal3 , Eric P. Xing4 , and Masashi Sugiyama2 1 Yahoo! Labs, 70 Add to Reading List Source URL: labs.yahoo.com Language: English - Date: 2014-02-26 18:29:12 Non-parametric statistics Dimension reduction Feature selection Model selection Kernel trick Lasso Kernel density estimation Supervised learning Least squares Statistics Regression analysis Machine learning
35	Neural Computation, vol.26, no.1, pp.84–131, Information-Maximization Clustering based on Squared-Loss Mutual Information∗ Add to Reading List Source URL: labs.yahoo.com Language: English - Date: 2014-02-26 18:28:23 Statistical theory Cluster analysis Data mining Geostatistics K-means clustering Kullback–Leibler divergence Mutual information Kernel density estimation Determining the number of clusters in a data set Statistics Multivariate statistics Machine learning
36	k -nearest neighbor estimation of entropies with confidence Kumar Sricharan∗ , Raviv Raich+ , Alfred O. Hero III∗ ∗ + Add to Reading List Source URL: web.eecs.umich.edu Language: English - Date: 2011-06-27 15:46:00 Statistical inference Information theory Randomness Maximum likelihood Estimator Normal distribution Kernel density estimation Entropy Differential entropy Statistics Statistical theory Estimation theory
37	PDF Document Add to Reading List Source URL: www.stat.rice.edu Language: English - Date: 2015-03-14 12:18:09 Regression analysis Computational statistics Kernel density estimation Econometrics Nonparametric regression Bootstrapping Kernel regression K-nearest neighbor algorithm Polynomial regression Statistics Non-parametric statistics Statistical inference
38	A Novel Bayesian Approach to Adaptive Mean Shift Segmentation of Brain Images Qaiser Mahmood, Artur Chodorowski, Andrew Mehnert, Mikael Persson Department of Signals and Systems, MedTech West, Chalmers University of Tech Add to Reading List Source URL: www.medtechwest.se Language: English - Date: 2012-08-30 06:11:02 Image processing Geostatistics Multivariate statistics K-nearest neighbor algorithm Kernel density estimation Segmentation Statistical classification K-means clustering Density estimation Statistics Non-parametric statistics Machine learning
39	Noname manuscript No. (will be inserted by the editor) A survey of the state of the art in learning the kernels M. Ehsan Abbasnejad1 · Dhanesh Ramachandram2 · Rajeswari Mandava3 Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2015-03-17 00:39:18 Non-parametric statistics Kernel density estimation Kernel trick Fisher kernel Support vector machine Kernel Reproducing kernel Hilbert space Linux kernel Supervised learning Statistics Machine learning Statistical classification
40	Locating Nearby Sources of Air Pollution by Nonparametric Regression of Atmospheric Concentrations on Wind Direction Ronald C. Henry Yu-Shuo Chang Add to Reading List Source URL: www.nrcse.washington.edu Language: English - Date: 2001-09-21 14:37:09 Econometrics Regression analysis Statistical methods Nonparametric regression Gaussian function Kernel density estimation Bootstrapping Confidence interval Kernel smoother Statistics Non-parametric statistics Statistical inference

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