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Shape constraints yield flexible middle grounds between fully nonparametric and fully parametric approaches to modeling distributions of data.
1903
Earlier work this paper cites.
Jones, M., Marron, J. S., and Park, B. U. (1991), “A Simple Root n n Bandwidth Selector,” The Annals of Statistics
1932
Earlier work this paper cites.
Rockafellar, R. T. (1997), Convex analysis. Reprint of the 1970 original
1970
Earlier work this paper cites.
Prékopa, A. (1973), “On Logarithmic Concave Measures and Functions,” Acta Scientiarum Mathematicarum
1973
Earlier work this paper cites.
Rudemo, M. (1982), “Empirical Choice of Histograms and Kernel Density Estimators,” Scandinavian Journal of Statistics
1982
Earlier work this paper cites.
Bowman, A. W. (1984), “An Alternative Method of Cross-Validation for the Smoothing of Density Estimates,” Biometrika
1984
Earlier work this paper cites.
Wand, M. P. and Jones, M. C. (1994), “Multivariate Plug-In Bandwidth Selection,” Computational Statistics
1994
Earlier work this paper cites.
Wong, W. H. and Shen, X. (1995), “Probability Inequalities for Likelihood Ratios and Convergence Rates of Sieve MLEs,” The Annals of Statistics
1995
Earlier work this paper cites.
An, M. Y. (1997), “Log-Concave Probability Distributions: Theory and Statistical Testing,” Duke University Dept of Economics Working Paper
1997
Earlier work this paper cites.
Kappel, F. and Kuntsevich, A. V. (2000), “An Implementation of Shor’s r-Algorithm,” Computational Optimization and Applications
2000
Earlier work this paper cites.
Venables, W. N. and Ripley, B. D. (2002), Modern Applied Statistics with S
2002
Earlier work this paper cites.
Duong, T. and Hazelton, M. L. (2003), “Plug-In Bandwidth Matrices for Bivariate Kernel Density Estimation,” Journal of Nonparametric Statistics
2003
Earlier work this paper cites.
Bagnoli, M. and Bergstrom, T. (2005), “Log-Concave Probability and its Applications,” Economic Theory
2005
Earlier work this paper cites.
— (2005), “Cross-Validation Bandwidth Matrices for Multivariate Kernel Density Estimation,” Scandinavian Journal of Statistics
2005
Earlier work this paper cites.
2007
Cited alongside, same era.
Cule, M., Gramacy, R., and Samworth, R. (2009), “LogConcDEAD: An R Package for Maximum Likelihood Estimation of a Multivariate Log-Concave Density,” Journal of Statistical Software
2009
Cited alongside, same era.
Genz, A. and Bretz, F. (2009), Computation of Multivariate Normal and t Probabilities
2009
Cited alongside, same era.
Chacón, J. E. and Duong, T. (2010), “Multivariate Plug-In Bandwidth Selection with Unconstrained Pilot Bandwidth Matrices,” Test
2010
Cited alongside, same era.
Cule, M. and Samworth, R. (2010), “Theoretical Properties of the Log-Concave Maximum Likelihood Estimator of a Multidimensional Density,” Electronic Journal of Statistics
Kim, A. K. and Samworth, R. J. (2016), “Global Rates of Convergence in Log-Concave Density Estimation,” Annals of Statistics
2016
Later among the works it cites.
Scrucca, L., Fop, M., Murphy, T. B., and Raftery, A. E. (2016), “mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models,” The R Journal
2016
Later among the works it cites.
Koenker, R. and Mizera, I. (2018), “Shape Constrained Density Estimation via Penalized Rényi Divergence,” Statistical Science
2018
Later among the works it cites.
Samworth, R. J. (2018), “Recent progress in log-concave density estimation,” Statistical Science
2018
Later among the works it cites.
Schubert, M. (2019), “clustermq Enables Efficient Parallelisation of Genomic Analyses,” Bioinformatics
2019
Later among the works it cites.
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2010
Cited alongside, same era.
Cule, M., Samworth, R., and Stewart, M. (2010), “Maximum Likelihood Estimation of a Multi-Dimensional Log-Concave Density,” Journal of the Royal Statistical Society: Series B (Statistical Methodology)
2010
Cited alongside, same era.
Carroll, R. J., Delaigle, A., and Hall, P. (2011), “Testing and Estimating Shape-Constrained Nonparametric Density and Regression in the Presence of Measurement Error,” Journal of the American Statistical Association
2011
Cited alongside, same era.
Dümbgen, L. and Rufibach, K. (2011), “logcondens: Computations Related to Univariate Log-Concave Density Estimation,” Journal of Statistical Software
2011
Cited alongside, same era.
Hazelton, M. L. (2011), “Assessing Log-Concavity of Multivariate Densities,” Statistics & Probability Letters
2011
Cited alongside, same era.
Shor, N. Z. (2012), Minimization Methods for Non-Differentiable Functions
2012
Cited alongside, same era.
Chen, Y. and Samworth, R. J. (2013), “Smoothed Log-Concave Maximum Likelihood Estimation with Applications,” Statistica Sinica
2013
Cited alongside, same era.
Towns, J., Cockerill, T., Dahan, M., Foster, I., Gaither, K., Grimshaw, A., Hazlewood, V., Lathrop, S., Lifka, D., Peterson, G. D., Roskies, R., Scott, J. R., and Wilkins-Diehr, N. (2014), “XSEDE: Accelerating Scientific Discovery,” Computing in Science & Engineering
2014
Cited alongside, same era.
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L. D., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T. L., Miller, E., Bache, S. M., Müller, K., Ooms, J., Robinson, D., Seidel, D. P., Spinu, V., Takahashi, K., Vaughan, D., Wilke, C., Woo, K., and Yutani, H. (2019), “Welcome to the tidyverse,” Journal of Open Source Software
2019
Later among the works it cites.
Nagler, T. and Vatter, T. (2020), kde1d: Univariate Kernel Density Estimation
2020
Later among the works it cites.
Wasserman, L., Ramdas, A., and Balakrishnan, S. (2020), “Universal Inference,” Proceedings of the National Academy of Sciences
2020
Later among the works it cites.
Barber, R. F. and Samworth, R. J. (2021), “Local continuity of log-concave projection, with applications to estimation under model misspecification,” Bernoulli
2021
Closest in time.
2021
Closest in time.
Dowle, M. and Srinivasan, A. (2021), data.table: Extension of ‘data.frame’
2021
Closest in time.
Duong, T. (2021), ks: Kernel Smoothing
2021
Closest in time.
Genz, A., Bretz, F., Miwa, T., Mi, X., Leisch, F., Scheipl, F., and Hothorn, T. (2021), mvtnorm: Multivariate Normal and t Distributions
2021
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R Core Team (2021), R: A Language and Environment for Statistical Computing
2021
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