A fast and objective multidimensional kernel density estimation method: FastKDE

Computational Statistics and Data Analysis

Volumn 101, Issue , 2016, Pages 148-160

  O'Brien, Travis A ^a,b   Kashinath, Karthik ^a   Cavanaugh, Nicholas R ^a   Collins, William D ^a,c   O'Brien, John P ^a,d  

^a LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

ECF; Empirical characteristic function; Histogram; KDE; Kernel density estimation; Multidimensional; Nonuniform FFT; NuFFT

Indexed keywords

BANDWIDTH; ESTIMATION; GRAPHIC METHODS; STATISTICAL METHODS; STATISTICS;

EMPIRICAL CHARACTERISTIC FUNCTION; HISTOGRAM; KERNEL DENSITY ESTIMATION; MULTIDIMENSIONAL; NUFFT;

PROBABILITY DENSITY FUNCTION;

EID: 84962246335     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2016.02.014     Document Type: Article

References (23)

1. A. AghaKouchak, L. Cheng, O. Mazdiyasni, and A. Farahmand Global warming and changes in risk of concurrent climate extremes: Insights from the 2014 California drought Geophys. Res. Lett. 1944-8007 41 24 2014 8847 8852 10.1002/2014GL062308
2. A. Bernacchia, and S. Pigolotti Self-consistent method for density estimation J. R. Stat. Soc. Ser. B Stat. Methodol. 1467-9868 73 3 2011 407 422 10.1111/j.1467-9868.2011.00772.x
3. S. Bony, J.-L. Dufresne, H. Le Treut, J.-J. Morcrette, and C. Senior On dynamic and thermodynamic components of cloud changes Clim. Dynam. 1432-0894 22 2-3 2004 71 86 10.1007/s00382-003-0369-6
4. C. Deser, and A.S. Phillips Simulation of the 1976/77 climate transition over the north pacific: Sensitivity to tropical forcing J. Clim. 1520-0442 19 23 2006 6170 6180 10.1175/jcli3963.1
5. T. Duong, and M.L. Hazelton Cross-validation bandwidth matrices for multivariate kernel density estimation Scand. J. Statist. 1467-9469 32 3 2005 485 506 URL: http://dx.doi.org/10.1111/j.1467-9469.2005.00445.x
6. L. Greengard, and J.-Y. Lee Accelerating the nonuniform fast Fourier transform SIAM Rev. 46 3 2004 443 454 10.1137/S003614450343200X URL: http://epubs.siam.org/doi/abs/10.1137/S003614450343200X
7. N.-B. Heidenreich, A. Schindler, and S. Sperlich Bandwidth selection for kernel density estimation: a review of fully automatic selectors AStA Adv. Stat. Anal. 1863-818X 97 4 2013 403 433 10.1007/s10182-013-0216-y
8. M. Hilbert, and P. López The world's technological capacity to store, communicate, and compute information Science 332 6025 2011 60 65 10.1126/science.1200970 URL: http://www.sciencemag.org/content/332/6025/60.abstract
9. T. Karl, W. Koss N. C. D. C. (US) Regional and National Monthly, Seasonal, and Annual Temperature Weighted by Area, 1895-1983 Historical Climatology Series 1984 National Climatic Data Center URL: https://books.google.com/books?id=3OjSHAAACAAJ
10. V.E. Larson, J.-C. Golaz, and W.R. Cotton Small-scale and mesoscale variability in cloudy boundary layers: Joint probability density functions J. Atmos. Sci. 1520-0469 59 24 2002 3519 3539 http://dx.doi.org/10.1175/1520-0469(2002)059<3519:SSAMVI>2.0.CO;2
11. H. Lee, J. Kim, D.E. Waliser, P.C. Loikith, C.A. Mattmann, and S. McGinnis Using joint probability distribution functions to evaluate simulations of precipitation, cloud fraction and insolation in the North America Regional Climate Change Assessment Program (NARCCAP) Clim. Dynam. 1432-0894 45 1-2 2014 309 323 10.1007/s00382-014-2253-y
12. J. Luedicke, and A. Bernacchia Self-consistent density estimation Stata J. 14 2 2014 237 258 (22). URL: http://www.stata-journal.com/article.html?article=st0334
13. R. Marchand, T. Ackerman, M. Smyth, and W.B. Rossow A review of cloud top height and optical depth histograms from MISR, ISCCP, and MODIS J. Geophys. Res. 0148-0227 115 D16 2010 1 25 10.1029/2009jd013422
14. Nagler, T., Czado, C., (in preparation). Evading the curse of dimensionality in multivariate kernel density estimation with simplified vines, arXiv Preprint arXiv:1503.03305.
15. T.A. O'Brien, W.D. Collins, S.A. Rauscher, and T.D. Ringler Reducing the computational cost of the ECF using a nuFFT: A fast and objective probability density estimation method Comput. Statist. Data Anal. 0167-9473 79 2014 222 234 URL: http://www.sciencedirect.com/science/article/pii/S016794731400173X
16. Pachauri, R.K., Allen, M., Barros, V., Broome, J., Cramer, W., Christ, R., Church, J., Clarke, L., Dahe, Q., Dasgupta, P., et al. 2014. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.
17. C. Schumacher, and R.A. Houze Stratiform rain in the tropics as seen by the TRMM precipitation Radar∗ J. Clim. 1520-0442 16 11 2003 1739 1756 http://dx.doi.org/10.1175/1520-0442(2003)016<1739:SRITTA>2.0.CO;2
18. D.W. Scott The curse of dimensionality and dimension reduction Multivariate Density Estimation 2008 John Wiley & Sons, Inc. 195 217 URL: http://dx.doi.org/10.1002/9780470316849.ch7
19. B.W. Silverman Density Estimation for Statistics and Data Analysis, Vol. 26 1986 CRC Press
20. T.M. Smith, R.W. Reynolds, T.C. Peterson, and J. Lawrimore Improvements to NOAA's historical merged land-ocean surface temperature analysis (1880-2006) J. Clim. 1520-0442 21 10 2008 2283 2296 10.1175/2007jcli2100.1
21. M. Wand, and M. Jones Kernel Smoothing Monographs on Statistics and Applied Probability vol. 60 1995 Chapman & Hall London
22. M.P. Wand, J.S. Marron, and D. Ruppert Transformations in density estimation J. Amer. Statist. Assoc. 1537-274X 86 414 1991 343 353 10.1080/01621459.1991.10475041
23. E. Wit, E.v.d. Heuvel, and J.-W. Romeijn All models are wrong.: an introduction to model uncertainty Stat. Neerl. 0039-0402 66 3 2012 217 236 10.1111/j.1467-9574.2012.00530.x