Variable Kernel Estimates of Multivariate Densities

On Estimation of a Probability Density Function and Mode

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An Algorithm for Finding Best Matches in Logarithmic Expected Time

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A Nonparametric Estimate of a Multivariate Density Function

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Nonparametric probability density estimation

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Characterization of cyclostationary random signal processes

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Patterns in pattern recognition: 1968-1974

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Nonparametric Probability Density Estimation: I. A Summary of Available Methods

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Frontiers of Pattern Recognition

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Nonparametric estimates of probability densities

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A HIERARCHY OF PROBABILITY DENSITY FUNCTION ESTIMATES

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Speech enhancement in discontinuous transmission systems using the constrained-stability least-mean-squares algorithm

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Self-tuning density estimation based on Bayesian averaging of adaptive kernel density estimations yields state-of-the-art performance

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Parallel heuristic search strategy based on a Bayesian approach for simultaneous recognition of contaminant sources and aquifer parameters at DNAPL-contaminated sites

Lu, W., Wang, H., & Li, J. (2020) · Environmental Science and Pollution Research · doi:10.1007/s11356-020-09382-z · Cited by 13

Nonparametric density estimation with adaptive varying window size

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Sequential and recursive estimators of the probability density

Wertz, W. (1985) · Statistics · doi:10.1080/02331888508801856 · Cited by 14

Ake: An R Package for Discrete and Continuous Associated Kernel Estimations

Wanbitching, E. W., Somé, S. M., & Kokonendji, C. C. (2016) · The R Journal · doi:10.32614/rj-2016-045 · Cited by 14

A Flexible Method for Estimating Luminosity Functions via Kernel Density Estimation

Yuan, Z., Jarvis, M. J., & Wang, J. (2020) · The Astrophysical Journal Supplement Series · doi:10.3847/1538-4365/ab855b · Cited by 15

Detecting and Visualizing Observation Hot-Spots in Massive Volunteer-Contributed Geographic Data across Spatial Scales Using GPU-Accelerated Kernel Density Estimation

Zhang, G. (2022) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi11010055 · Cited by 13

On Mitigating Hard Clusters for Face Clustering

Chen, Y.-J., Zhong, H., Chen, C., Shen, C., Huang, J., Wang, T., Liang, Y. E., & Sun, Q. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19775-8_31 · Cited by 13

State of the art in photon density estimation

Hachisuka, T., Jarosz, W., Bouchard, G., Christensen, P. H., Frisvad, J. R., Jakob, W., Jensen, H. W., Kaschalk, M., Knaus, C., Selle, A. P., et al. (2012) · ACM SIGGRAPH Courses · doi:10.1145/2343483.2343489 · Cited by 13

On the risk of estimates for block decreasing densities

Gérard Biau, A., & Devroye, L. (2003) · Journal of Multivariate Analysis · doi:10.1016/s0047-259x(02)00028-3 · Cited by 13

Geostatistics in Historical Macroseismic Data Analysis

Danese, M., Lazzari, M., & Murgante, B. (2009) · Transactions on computational science · doi:10.1007/978-3-642-10649-1_19 · Cited by 12

CAKE: Convex Adaptive Kernel Density Estimation

Mahapatruni, R. S. G., & Gray, A. (2011) · International Conference on Artificial Intelligence and Statistics · Cited by 12

Local nearest neighbour classification with applications to semi-supervised learning

Cannings, T. I., Berrett, T. B., & Samworth, R. J. (2020) · The Annals of Statistics · doi:10.1214/19-aos1868 · Cited by 12

Statistical Risk Estimation for Communication System Design

Babuscia, A., & Cheung, K. (2012) · IEEE Systems Journal · doi:10.1109/jsyst.2012.2201889 · Cited by 12

Estimation of spatially distributed processes in wireless sensor networks with random packet loss

Ray, P., & Varshney, P. K. (2009) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2009.080836 · Cited by 12

An Improved Variable Kernel Density Estimator Based on L2 Regularization

Jin, Y., He, Y., & Huang, D. (2021) · Mathematics · doi:10.3390/math9162004 · Cited by 11

Estimating bivariate yield distributions and crop insurance premiums using nonparametric methods

Zheng, Q., Wang, H. H., & Shi, Q. H. (2014) · Applied Economics · doi:10.1080/00036846.2014.894630 · Cited by 11

Adaptive Kernel Density Estimation using Beta Kernel

Yin, X.-F., & Hao, Z. (2007) · International Conference on Machine Learning and Cybernetics · doi:10.1109/icmlc.2007.4370716 · Cited by 11

On bandwidth selection using minimal spanning tree for kernel density estimation

Sreevani, & Murthy, C. A. (2016) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2016.04.005 · Cited by 11

Nonparametric Multivariate Density Estimation: Case Study of Cauchy Mixture Model

Ruzgas, T., Lukauskas, M., & Čepkauskas, G. (2021) · Mathematics · doi:10.3390/math9212717 · Cited by 11

Integration of prior knowledge of measurement noise in kernel density classification

Li, Y., de Ridder, D., Duin, R. P. W., & Reinders, M. J. T. (2007) · Pattern Recognition · doi:10.1016/j.patcog.2007.05.005 · Cited by 12

Mining Contrast Subspaces

Duan, L., Tang, G., Pei, J., Bailey, J., Dong, G., Campbell, A., & Tang, C. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-06608-0_21 · Cited by 11

An adaptive method for bandwidth selection in circular kernel density estimation

Zámečník, S., Horová, I., Katina, S., & Hasilová, K. (2023) · Computational Statistics · doi:10.1007/s00180-023-01401-0 · Cited by 10

A bias corrected nonparametric regression estimator

Yao, W. (2011) · Statistics & Probability Letters · doi:10.1016/j.spl.2011.10.006 · Cited by 10

Earthquake prediction using the fields estimated by an adaptive algorithm

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Data classification with a relaxed model of variable kernel density estimation

Oyang, Y.-J., Ou, Y., Hwang, S., Chen, C., & Chang, D. T.-H. (2006) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2005.1556374 · Cited by 10

The Evaluation of Evidence for Auto-Correlated Data in Relation to Traces of Cocaine on Banknotes

Wilson, A. L., Aitken, C. G. G., Sleeman, R., & Carter, J. F. (2014) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.1111/rssc.12073 · Cited by 10

Density Estimation Using Exponentials of Orthogonal Series

Clutton-Brock, M. (1990) · Journal of the American Statistical Association · doi:10.1080/01621459.1990.10474937 · Cited by 10

Spatial and spatio-temporal point patterns on linear networks

Moradi, M. M. (2018) · Tesis Doctorals en Xarxa (Consorci de Serveis Universitaris de Catalunya) · doi:10.6035/14123.2018.685382 · Cited by 9

Exploration‐Based Statistical Learning for Selecting Kernel Density Estimates of Spatial Point Patterns

Govorov, M., Beconytė, G., & Анатольевич, Г. Г. (2025) · Transactions in GIS · doi:10.1111/tgis.70051 · Cited by 9

Location-adaptive density estimation and nearest-neighbor distance

Burman, P. J., & Nolan, D. (1992) · Journal of Multivariate Analysis · doi:10.1016/0047-259x(92)90095-w · Cited by 9

Asymptotic and qualitative performance of non-parametric density estimators: a comparative study

Takada, T. (2008) · Econometrics Journal · doi:10.1111/j.1368-423x.2008.00249.x · Cited by 9

Fuzzy importance sampling method for estimating failure possibility

Feng, K., Lü, Z., Ling, C., & Wang, L. (2020) · Fuzzy Sets and Systems · doi:10.1016/j.fss.2020.12.003 · Cited by 9

Hybrid semiparametric Bayesian networks

Atienza, D., Larrañaga, P., & Bielza, C. (2022) · Test · doi:10.1007/s11749-022-00812-3 · Cited by 9

Outlier Correction for Local Distance Measures in Example Based Speech Recognition

Wachter, M. D., Demuynck, K., & Compernolle, D. V. (2007) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2007.366942 · Cited by 9

Optimal bandwidth selection for variable kernel density estimates

Berlinet, A. F., Gérard Biau, A., & Laurent Rouvière, C. (2005) · Statistics & Probability Letters · doi:10.1016/j.spl.2005.04.036 · Cited by 9

Reducing the mean squared error in kernel density estimation

Kim, J., & Kim, C. (2013) · Journal of the Korean Statistical Society · doi:10.1016/j.jkss.2012.12.003 · Cited by 8

Probabilistic seismic hazard analysis using kernel density estimation technique for Chennai, India

Ramanna, C. K., & Dodagoudar, G. R. (2011) · Georisk Assessment and Management of Risk for Engineered Systems and Geohazards · doi:10.1080/17499518.2010.496073 · Cited by 8

Fast Nonparametric Density-Based Clustering of Large Datasets Using a Stochastic Approximation Mean-Shift Algorithm

Hyrien, O., & Baran, A. M. (2015) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.2015.1051625 · Cited by 8

In search of the optimal number of fund subgroups

Yan, C., & Cheng, T. (2019) · Journal of Empirical Finance · doi:10.1016/j.jempfin.2018.12.002 · Cited by 8

Selection of the Bandwidth Matrix in Spatial Varying Coefficient Models to Detect Anisotropic Regression Relationships

Hu, X., Lu, Y., Zhang, H., Jiang, H., & Shi, Q. (2021) · Mathematics · doi:10.3390/math9182343 · Cited by 8

Evaluation of typhoon-induced rainfall using nonparametric Monte Carlo simulation and locally weighted polynomial regression

Oh, T.-S., Moon, Y., & Kwon, H. (2010) · Hydrological Processes · doi:10.1002/hyp.7934 · Cited by 8

Some Improvement on Convergence Rates of Kernel Density Estimator

Xie, X., & Wu, J. (2014) · Applied Mathematics · doi:10.4236/am.2014.511161 · Cited by 8

Comparison of Neural Classification Algorithms Applied to Land Cover Mapping

Thiel, C., Giacco, F., Schwenker, F., & Günther, P. (2009) · Frontiers in artificial intelligence and applications · doi:10.3233/978-1-58603-984-4-254 · Cited by 8

DATAPLOT: A graphical display package for bacterial morphometry and fluorimetry data

Wilkinson, M. H. F., & Meijer, B. (1995) · Computer Methods and Programs in Biomedicine · doi:10.1016/0169-2607(95)01628-7 · Cited by 8

Variable Kernel Density Estimation in High-Dimensional Feature Spaces

der Walt, C. M. V., & Barnard, E. (2017) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v31i1.10885 · Cited by 8

On multivariate variable-kernel density estimates for time series

Tran, L. T. (1991) · Canadian Journal of Statistics · doi:10.2307/3315428 · Cited by 8

Bandwidth selection procedures tor kernel density estimates

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Dynamic Denoising of Tracking Sequences

Michailovich, O., & Tannenbaum, A. (2008) · IEEE Transactions on Image Processing · doi:10.1109/tip.2008.920795 · Cited by 8

A Graphical Analysis of the Interrelationships among Waterborne Asbestos, Digestive System Cancer and Population Density

Tarter, M. E., Cooper, R. C., & Freeman, W. R. (1983) · Environmental Health Perspectives · doi:10.1289/ehp.835379 · Cited by 8

Pattern Recognition in the Context of an Asbestos Cancer Threshold Study

Tarter, M. E. (1981) · Springer eBooks · doi:10.1007/978-1-4613-9464-8_15 · Cited by 8

Predictive inference with copulas for bivariate data

Muhammad, N. (2016) · UMP Institutional Repository (Universiti Malaysia Pahang) · Cited by 8

Max-Affine Spline Insights into Deep Generative NetworksPreprint

Balestriero, R., Paris, S., & Baraniuk, R. G. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2002.11912 · Cited by 8

Convergence de l'estimateur à noyau des k plus proches voisins en régression fonctionnelle non-paramétrique

Burba, F., Ferraty, F., & Vieu, P. (2008) · Comptes Rendus Mathématique · doi:10.1016/j.crma.2008.01.022 · Cited by 7

A brief survey on the choice of parameters for: “Kernel density estimation for time series data”

Semeyutin, A., & O’Neill, R. (2019) · The North American Journal of Economics and Finance · doi:10.1016/j.najef.2019.101038 · Cited by 7

Bootstrapping persistent Betti numbers and other stabilizing statistics

Roycraft, B., Krebs, J., & Polonik, W. (2023) · The Annals of Statistics · doi:10.1214/23-aos2277 · Cited by 7

Comparison study to bandwidth selection in binomial kernel estimation using Bayesian approaches

Zougab, N., Adjabi, S., & Kokonendji, C. C. (2015) · Journal of Statistical Theory and Practice · doi:10.1080/15598608.2015.1098579 · Cited by 7

Interactive local bandwidth choice

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Nonparametric density estimation and regression achieved with topographic maps maximizing the information-theoretic entropy of their outputs

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Statistical interpolation of FET data base measurements

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An Efficient Density-based Approach for Data Mining Tasks

Domeniconi, C., & Gunopulos, D. (2004) · Knowledge and Information Systems · doi:10.1007/s10115-003-0131-8 · Cited by 7

Bias reduction in nonparametric hazard rate estimation

Bagkavos, D. (2003) · University of Birmingham Institutional Research Archive (University of Birmingham) · Cited by 7

Bandwidth selection for kernel estimation in mixed multi-dimensional spacesPreprint

Bugeau, A., & Pérez, P. (2007) · arXiv (Cornell University) · doi:10.48550/arxiv.0709.1920 · Cited by 7

Asymptotic bias and variance for a general class of varying bandwidth density estimators

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Axiomatic Approach to Variable Kernel Density EstimationPreprint

Klebanov, I. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1805.01729 · Cited by 7

Consensus–relevance kNN and covariate shift mitigation

Kalpakis, K. (2023) · Machine Learning · doi:10.1007/s10994-023-06378-x · Cited by 6

Frequency-domain approach to automated and efficient multivariate kernel density estimation for probabilistic modeling

Zhang, F., Xu, J., & Wang, D. (2026) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2026.112351 · Cited by 6

JOW-y w gminach: lokalne partie władzy a nowe reguły rywalizacji

Flis, J., & Stolicki, D. M. (2017) · Ruch Prawniczy Ekonomiczny i Socjologiczny · doi:10.14746/rpeis.2017.79.3.20 · Cited by 6

Sparse reconstruction with spatial structures to automatically determine neighbors

Yu, W., Zhang, Y., Chen, Z., & Tinghua Ai, A. (2021) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2021.1885675 · Cited by 6

Ideal Bayesian Spatial Adaptation

Ročková, V., & Rousseau, J. (2023) · Journal of the American Statistical Association · doi:10.1080/01621459.2023.2241705 · Cited by 6

Regularization oversampling for classification tasks: To exploit what you do not know

der Schraelen, L. V., Stouthuysen, K., Broucke, S. V., & Verdonck, T. (2023) · Information Sciences · doi:10.1016/j.ins.2023.03.146 · Cited by 6

Piecewise Linear Models with Guaranteed Closeness to the Data

Latecki, L. J., Sobel, M., & Lakaemper, R. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2009.13 · Cited by 6

Parameterless Semi-supervised Anomaly Detection in Univariate Time Series

Iegorov, O., & Fischmeister, S. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-67658-2_37 · Cited by 6

On the convergence of kernel estimators of probability density functions

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Discrimination and classification: Overview

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Kernel regression networks with local structural information and covariance volume adaptation

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Computational procedure for maximum penalized likelihood estimate

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Group assessment of multivariate prior distributions

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Classification procedures using multivariate variable kernel density estimate

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A NEW ALGORITHM FOR ESTIMATING THE RISK OF NATURAL DISASTERS WITH INCOMPLETE DATA

Leung, Y., & Huang, C. (2000) · International Journal of General Systems · doi:10.1080/03081070008960929 · Cited by 5

Mapping Entity Sets in News Archives Across Time

Duan, Y., Jatowt, A., Bhowmick, S. S., & Yoshikawa, M. (2019) · Data Science and Engineering · doi:10.1007/s41019-019-00102-3 · Cited by 5

Ranking Molecules with Vanishing Kernels and a Single Parameter: Active Applicability DomainIncluded

Berenger, F., & Yamanishi, Y. (2020) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.9b01075 · Cited by 6

Not All Trips are Equal

Chong, W.-H., Dai, B. T., & Lim, E. (2015) · Conference on Online Social Networks · doi:10.1145/2817946.2817958 · Cited by 5

Efficiencies for window estimates of the parameters of the Cauchy distribution

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Transformations in semi-parametric Bayesian synthetic likelihood

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Estimation of densities of probability and regression surfaces in one or two dimensions

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A study on discriminant analysis techniques applied to multivariate lognormal data

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A Study on Special Quality of Hourly Precipitation of Typhoon happened in Korea

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Using pseudometrics in kernel density estimation

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Color Image Segmentation Using Multilevel Clustering Approach

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Population Synthesis via k-Nearest Neighbor Crossover Kernel

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Numerical results concerning a sharp adaptive density estimator

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GeoVis: a data-driven geographic visualization recommendation system via latent space encoding

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Mode testing via higher-order density estimation

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Nonparametric conditional density estimation of short-term interest rate movements: procedures, results and risk management implications

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A Likelihood-Tuned Density Estimator Via a Nonparametric Mixture Model

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A data-driven kernel estimator of the density function

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On Statistics and Dynamics of Cosmic Structure

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Graphical analysis and financial classification: A case study

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A NOTE ON THE USEFULNESS OF SUIPERKERNELS IN DENSITY ESTIMATION' BY Luc DEVROYE

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A Note on the Usefulness of Superkernels in Density Estimation

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The strong uniform convergence of multivariate variable kernel estimates

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A comparative study of some kernel-based nonparametric density estimators

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A nonparametric data based univariate density function estimate

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