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Multivariate k-nearest neighbor density estimates
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Cited by:
- Devroye, Luc & Krzyzak, Adam, 2002. "New Multivariate Product Density Estimators," Journal of Multivariate Analysis, Elsevier, vol. 82(1), pages 88-110, July.
- Burman, Prabir, 2002. "Estimation of equifrequency histograms," Statistics & Probability Letters, Elsevier, vol. 56(3), pages 227-238, February.
- Fan, Yanqin & Hou, Lei & Yan, Karen X., 2018. "On the density estimation of air pollution in Beijing," Economics Letters, Elsevier, vol. 163(C), pages 110-113.
- Chu, Ba & Jacho-Chávez, David T., 2012. "k-NEAREST NEIGHBOR ESTIMATION OF INVERSE-DENSITY-WEIGHTED EXPECTATIONS WITH DEPENDENT DATA," Econometric Theory, Cambridge University Press, vol. 28(4), pages 769-803, August.
- Lucio Barabesi, 2001. "Local parametric density estimation methods in line transect sampling," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1-2), pages 22-38.
- Cheng, Philip E., 1995. "A note on strong convergence rates in nonparametric regression," Statistics & Probability Letters, Elsevier, vol. 24(4), pages 357-364, September.
- repec:jss:jstsof:33:i04 is not listed on IDEAS
- Devroye, Luc & Krzyzak, Adam, 1999. "On the Hilbert kernel density estimate," Statistics & Probability Letters, Elsevier, vol. 44(3), pages 299-308, September.
- Onur Genç & Ali Dağ, 2016. "A machine learning-based approach to predict the velocity profiles in small streams," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(1), pages 43-61, January.
- Zheng Li & Guannan Liu & Qi Li, 2017. "Nonparametric Knn estimation with monotone constraints," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 988-1006, October.
- Kung, Yi-Hung & Lin, Pei-Sheng & Kao, Cheng-Hsiung, 2012. "An optimal k-nearest neighbor for density estimation," Statistics & Probability Letters, Elsevier, vol. 82(10), pages 1786-1791.
- Wang, Xiaogang & Qiu, Weiliang & Zamar, Ruben H., 2007. "CLUES: A non-parametric clustering method based on local shrinking," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 286-298, September.
- Boyang Shang & Daniel W. Apley & Sanjay Mehrotra, 2023. "Diversity Subsampling: Custom Subsamples from Large Data Sets," INFORMS Joural on Data Science, INFORMS, vol. 2(2), pages 161-182, October.
- Aya-Moreno, Carlos & Geenens, Gery & Penev, Spiridon, 2018. "Shape-preserving wavelet-based multivariate density estimation," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 30-47.
- Kohtaro Hitomi & Masamune Iwasawa & Yoshihiko Nishiyama, 2018. "Rate Optimal Specification Test When the Number of Instruments is Large," KIER Working Papers 986, Kyoto University, Institute of Economic Research.
- Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
- Sain, Stephan R., 2002. "Multivariate locally adaptive density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 39(2), pages 165-186, April.
- Tomasz Jetka & Karol Nienałtowski & Tomasz Winarski & Sławomir Błoński & Michał Komorowski, 2019. "Information-theoretic analysis of multivariate single-cell signaling responses," PLOS Computational Biology, Public Library of Science, vol. 15(7), pages 1-23, July.
- Chang, Fang & Qiu, Weiliang & Zamar, Ruben H. & Lazarus, Ross & Wang, Xiaogang, 2010. "clues: An R Package for Nonparametric Clustering Based on Local Shrinking," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i04).
- Xinyang Yu & Cheng Wang & Zhongqing Yang & Binyan Jiang, 2022. "Tuning selection for two-scale kernel density estimators," Computational Statistics, Springer, vol. 37(5), pages 2231-2247, November.
- Penrose, Mathew D., 2000. "Central limit theorems for k-nearest neighbour distances," Stochastic Processes and their Applications, Elsevier, vol. 85(2), pages 295-320, February.
- Gery Geenens & Arthur Charpentier & Davy Paindaveine, 2014. "Probit Transformation for Nonparametric Kernel Estimation of the Copula Density," Working Papers ECARES ECARES 2014-23, ULB -- Universite Libre de Bruxelles.
- Onur Genç & Ali Dağ, 2016. "A machine learning-based approach to predict the velocity profiles in small streams," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(1), pages 43-61, January.
- Hino, Hideitsu & Koshijima, Kensuke & Murata, Noboru, 2015. "Non-parametric entropy estimators based on simple linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 72-84.
- Dmitri Pavlov & Svetla Slavova & Richard J. Kryscio, 2009. "Estimating Relative Risk on the Line Using Nearest Neighbor Statistics," Methodology and Computing in Applied Probability, Springer, vol. 11(2), pages 249-265, June.
- Gery Geenens, 2014. "Probit Transformation for Kernel Density Estimation on the Unit Interval," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 346-358, March.