The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R
Open accessAbstract
Kernel smoothing is one of the most widely used non-parametric data smoothing techniques. We introduce a new R package ks for multivariate kernel smoothing. Currently it contains functionality for kernel density estimation and kernel discriminant analysis. It is a comprehensive package for bandwidth matrix selection, implementing a wide range of data-driven diagonal and unconstrained bandwidth selectors.
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Citations
Cites
A Reliable Data-Based Bandwidth Selection Method for Kernel Density Estimation
Sheather, S. J., & Jones, M. C. (1991) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1991.tb01857.x · Cited by 2,641
Smoothing Methods in Statistics
Yandell, B. S. (1997) · Technometrics · doi:10.1080/00401706.1997.10485134 · Cited by 1,295
An alternative method of cross-validation for the smoothing of density estimates
BOWMAN, A. W. (1984) · Biometrika · doi:10.1093/biomet/71.2.353 · Cited by 934
Computing and Graphing Highest Density Regions
Hyndman, R. J. (1996) · The American Statistician · doi:10.1080/00031305.1996.10474359 · Cited by 720
Empirical Choice of Histograms and Kernel Density Estimators
Rudemo, M. (1982) · Cited by 719
Cross-validation Bandwidth Matrices for Multivariate Kernel Density Estimation
DUONG, T., & HAZELTON, M. L. (2005) · Scandinavian Journal of Statistics · doi:10.1111/j.1467-9469.2005.00445.x · Cited by 317
Self-citationMultivariate plug-in bandwidth selection
WAND, M. P., & Jones, C. L. (1994) · Open Research Online (The Open University) · Cited by 305
Plug-in bandwidth matrices for bivariate kernel density estimation
Duong, T., & Hazelton, M. (2003) · Journal of Nonparametric Statistics · doi:10.1080/10485250306039 · Cited by 303
Self-citationHall, P., Marron, J. S., & Park, B. U. (1992) · Probability Theory and Related Fields · doi:10.1007/bf01205233 · Cited by 248
Cross-Validation of Multivariate Densities
Sain, S. R., Baggerly, K. A., & Scott, D. W. (1994) · Journal of the American Statistical Association · doi:10.1080/01621459.1994.10476814 · Cited by 228
Cited by
NBB-Psy, Böttcher, C., Schlickeiser, S., Sneeboer, M. A. M., Kunkel, D., Knop, A., Paza, E., Fidzinski, P., Kraus, L., Snijders, G. J. L., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-018-0290-2 · Cited by 436
Nebulosa recovers single-cell gene expression signals by kernel density estimation
Alquicira-Hernandez, J., & Powell, J. E. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab003 · Cited by 381
The natverse, a versatile toolbox for combining and analysing neuroanatomical data
Bates, A. S., Manton, J. D., Jagannathan, S. R., Costa, M., Schlegel, P., Rohlfing, T., & Jefferis, G. S. (2020) · eLife · doi:10.7554/elife.53350 · Cited by 215
Stochastic earned value analysis using Monte Carlo simulation and statistical learning techniques
Acebes, F., Pereda, M., Poza, D., Pajares, J., & Galán, J. M. (2015) · International Journal of Project Management · doi:10.1016/j.ijproman.2015.06.012 · Cited by 120
Spatial Guilds in the Serengeti Food Web Revealed by a Bayesian Group Model
Baskerville, E. B., Dobson, A. P., Bedford, T., Allesina, S., Anderson, T. M., & Pascual, M. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002321 · Cited by 113
“Color brightness indicates posterior density, estimated using the ks multivariate kernel density estimation package for R [68].”
Method
Metadata
- Authors
- Duong, T.
- Venue
- Journal of Statistical Software
- Publisher
- Foundation for Open Access Statistic
- Published
- 2007
- Volume
- 21
- Issue
- 7
- ISSN
- 1548-7660 (ISSN-L)
- OpenAlex
- W1905316980
- Cited by
- 593
- References
- 12
- FWCI
- 5.91
- Type
- journal article
- Language
- en
- Open access
- diamond
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- Duong, T. (2007). ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R. Journal of Statistical Software. https://doi.org/10.18637/jss.v021.i07
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
