Cross-validation Bandwidth Matrices for Multivariate Kernel Density Estimation
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- Yuji Sakamoto & Nakahiro Yoshida, 2004. "Asymptotic expansion formulas for functionals of ε-Markov processes with a mixing property," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 56(3), pages 545-597, September.
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- Billings, Stephen B. & Johnson, Erik B., 2012.
"A non-parametric test for industrial specialization,"
Journal of Urban Economics,
Elsevier, vol. 71(3), pages 312-331.
- Stephen B. Billings & Erik B. Johnson, 2010. "A nonparametric test for industrial specialization," Working Papers 2010/40, Institut d'Economia de Barcelona (IEB).
- Gramacki, Artur & Gramacki, Jarosław, 2017. "FFT-based fast bandwidth selector for multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 27-45.
- Rob J. Hyndman & Han Lin Shang, 2008. "Rainbow plots, Bagplots and Boxplots for Functional Data," Monash Econometrics and Business Statistics Working Papers 9/08, Monash University, Department of Econometrics and Business Statistics.
- O’Brien, Travis A. & Kashinath, Karthik & Cavanaugh, Nicholas R. & Collins, William D. & O’Brien, John P., 2016. "A fast and objective multidimensional kernel density estimation method: fastKDE," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 148-160.
- J. Chacón & T. Duong, 2010. "Multivariate plug-in bandwidth selection with unconstrained pilot bandwidth matrices," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(2), pages 375-398, August.
- Seppo Pulkkinen & Marko Mäkelä & Napsu Karmitsa, 2013. "A continuation approach to mode-finding of multivariate Gaussian mixtures and kernel density estimates," Journal of Global Optimization, Springer, vol. 56(2), pages 459-487, June.
- Hu, Shuowen & Poskitt, D.S. & Zhang, Xibin, 2012.
"Bayesian adaptive bandwidth kernel density estimation of irregular multivariate distributions,"
Computational Statistics & Data Analysis,
Elsevier, vol. 56(3), pages 732-740.
- Shuowen Hu & D.S. Poskitt & Xibin Zhang, 2010. "Bayesian Adaptive Bandwidth Kernel Density Estimation of Irregular Multivariate Distributions," Monash Econometrics and Business Statistics Working Papers 21/10, Monash University, Department of Econometrics and Business Statistics.
- Duong, Tarn & Cowling, Arianna & Koch, Inge & Wand, M.P., 2008. "Feature significance for multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4225-4242, May.
- Zougab, Nabil & Adjabi, Smail & Kokonendji, Célestin C., 2014. "Bayesian estimation of adaptive bandwidth matrices in multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 28-38.
- repec:bla:istatr:v:84:y:2016:i:3:p:413-433 is not listed on IDEAS
- Tiee-Jian Wu & Chih-Yuan Hsu & Huang-Yu Chen & Hui-Chun Yu, 2014. "Root $$n$$ n estimates of vectors of integrated density partial derivative functionals," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(5), pages 865-895, October.
- Horová, Ivana & Koláček, Jan & Vopatová, Kamila, 2013. "Full bandwidth matrix selectors for gradient kernel density estimate," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 364-376.
- Nicolai, R.P. & Koning, A.J., 2006. "A general framework for statistical inference on discrete event systems," Econometric Institute Research Papers EI 2006-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Pulkkinen, Seppo, 2015. "Ridge-based method for finding curvilinear structures from noisy data," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 89-109.
- Filippone, Maurizio & Sanguinetti, Guido, 2011. "Approximate inference of the bandwidth in multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3104-3122, December.
- Isabel Fuentes-Santos & Wenceslao González-Manteiga & Jorge Mateu, 2016. "Consistent Smooth Bootstrap Kernel Intensity Estimation for Inhomogeneous Spatial Poisson Point Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 416-435, June.
- Bongiorno, Enea G. & Goia, Aldo, 2016. "Classification methods for Hilbert data based on surrogate density," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 204-222.
- Hazelton, Martin L. & Cox, Murray P., 2016. "Bandwidth selection for kernel log-density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 56-67.
- repec:eee:csdana:v:119:y:2018:i:c:p:139-154 is not listed on IDEAS
- Schoch, Tobias & Staub, Kaspar & Pfister, Christian, 2012. "Social inequality and the biological standard of living: An anthropometric analysis of Swiss conscription data, 1875–1950," Economics & Human Biology, Elsevier, vol. 10(2), pages 154-173.
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