José E. Chacón

José E. Chacón

Professor of Statistics

University of Extremadura

Biography

José E. Chacón is a Professor of Statistics at the Department of Mathematics and a member of the Institute of Mathematics of the University of Extremadura. His research interests include nonparametric kernel smoothing, cluster analysis and mathematical statistics.

Interests

  • Kernel Smoothing
  • Cluster Analysis
  • Mathematical Statistics

Education

  • PhD in Statistics, 2004

    Universidad de Extremadura

Publications

(2022). Bump hunting through density curvature features. Preprint.

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(2022). Introduction to the special issue on Data Science for COVID-19. Journal of Nonparametric Statistics, 34, 555–569.

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(2022). A new selection criterion for statistical home range estimation. Journal of Applied Statistics, 49, 722–737.

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(2022). Minimum adjusted Rand index for two clusterings of a given size. Advances in Data Analysis and Classification.

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(2021). Explicit agreement extremes for a 2x2 table with given marginals. Journal of Classification, 38, 257–263.

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(2021). A close-up comparison of the misclassification error distance and the adjusted Rand index for external clustering evaluation. British Journal of Mathematical and Statistical Psychology, 74, 203–231.

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(2021). Statistical outline of animal home ranges: An application of set estimation. In Data Science: Theory and Applications (A.S.R. Srinivasa Rao and C.R. Rao, eds.). Handbook of Statistics, 44, 3–37.

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(2020). The modal age of Statistics. International Statistical Review, 88, 122–141.

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(2020). Modal clustering asymptotics with applications to bandwidth selection. Electronic Journal of Statistics, 14, 835–856.

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(2019). Mixture model modal clustering. Advances in Data Analysis and Classification, 13, 379–404.

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(2018). Multivariate Kernel Smoothing and Its Applications. Chapman & Hall.

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(2015). A population background for nonparametric density-based clustering. Statistical Science, 30, 518–532.

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(2014). A comparison of bandwidth selectors for mean shift clustering. In Theoretical and Applied Issues in Statistics and Demography (C. H. Skiadas, ed.), 47–59.

Preprint

(2014). Fourier methods for smooth distribution function estimation. Statistics & Probability Letters, 84, 223–230.

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(2013). Data-driven density derivative estimation, with applications to nonparametric clustering and bump hunting. Electronic Journal of Statistics, 7, 499–532.

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(2013). Data-Based Choice of the Number of Pilot Stages for Plug-in Bandwidth Selection. Communications in Statistics-Theory and Methods, 42, 2200–2214.

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(2012). Exact and Asymptotically Optimal Bandwidths for Kernel Estimation of Density Functionals. Methodology and Computing in Applied Probability, 14, 523–548.

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(2011). Asymptotics for general multivariate kernel density derivative estimators. Statistica Sinica, 21, 807–840.

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(2011). Gaussian kernels for density estimation with compositional data. Computers & Geosciences, 37, 702–711.

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(2011). Unconstrained Pilot Selectors for Smoothed Cross-validation. Australian & New Zealand Journal of Statistics, 53, 331–351.

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(2010). A note on the universal consistency of the kernel distribution function estimator. Statistics & Probability Letters, 80, 1414–1419.

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(2009). Data-driven choice of the smoothing parametrization for kernel density estimators. Canadian Journal of Statistics, 37, 249–265.

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(2009). Partial sufficiency and density estimation. Journal of Nonparametric Statistics, 21, 969–975.

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(2008). Bootstrap bandwidth selection using an h-dependent pilot bandwidth. Scandinavian Journal of Statistics, 35, 139–157.

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(2007). A note on kernel density estimation at a parametric rate. Journal of Nonparametric Statistics, 19, 13–21.

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(2007). On the existence and limit behavior of the optimal bandwidth for kernel density estimation. Statistica Sinica, 17, 289–300.

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(2007). On the use of Bayes factor in frequentist testing of a precise hypothesis. Communications in Statistics-theory and Methods, 36, 2251–2261.

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(2007). Stability under products of sufficient, minimal sufficient and complete sigma-fields in the Bayesian case. Statistics & Probability Letters, 77, 710–716.

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(2006). A note on minimal sufficiency. Statistica Sinica, 16, 7–14.

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(2005). On the L-1-consistency of wavelet density estimates. Canadian Journal of Statistics, 33, 489–496.

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