Research and Publications
Research Interests
My research interests include:
Statistics, Applied Statistics, Statistical Computing, Multivariate Analysis,
Multivariate Inference, GoodnessofFit, Nonlinear Dependence, Statistical Learning,
Cluster Analysis and Classification, Computational Statistics, and Energy Statistics.
Research Gate Profile
Books
Statistical Computing With R, Second Edition, Chapman & Hall/CRC, March 6, 2019.
Statistical Computing with R, Chapman & Hall/CRC (2008).
R by Example (with Jim Albert), Springer Use R! Series (2012).
Energy Statistics, Chapman & Hall/CRC: (forthcoming)
Research and software related to Estatistics
Estatistics (energy statistics, joint work with G. J. Szekely)
refers to a class of tests and statistics
based on Euclidean distances. Applications include testing
multivariate normality, multivariate distance components and
ksample test for equal distributions, hierarchical clustering by edistances,
multivariate independence tests, distance correlation, goodnessoffit tests.
Gabor J. Szekely,
National Science Foundation,
Maria L. Rizzo,
Bowling Green State University.
R software: Energy statistics are implemented in the contributed
package
energy for R.
See GitHub account mariarizzo for
updates under development.
References

Songzi Li and Maria L. Rizzo (2017). Kgroups: A Generalization of Kmeans Clustering,
ArXiv eprints, 1711.04359,
pdf.

M. L. Rizzo and J. T. Haman (2016).
Expected distances and goodnessoffit for the asymmetric Laplace distribution,
Statistics & Probability Letters,
Volume 117, pp. 158164, ISSN 01677152,
http://dx.doi.org/10.1016/j.spl.2016.05.006.

G. J. Szekely and M. L. Rizzo (2017). The Energy of Data,
The Annual Review of Statistics and Its Applications. Extended Review.
4:447479. , doi: 10.1146/annurevstatistics060116054026

G. J. Szekely and M. L. Rizzo (2015).
“Partial Distance Correlation”, in Nonparametric Statistics2nd ISNPS Conference,
Cádiz, 2014. Springer. 179190.

G. J. Szekely and M. L. Rizzo.
Partial Distance Correlation,
Proceedings of the 2nd International Conference
on Nonparametric Statistics, Springer (to appear).

M. L. Rizzo and G. J. Szekely (2016).
Energy Distance, WIRES Computational Statistics,
Wiley, Volume 8 Issue 1, 2738.
Available online Dec., 2015, doi: 10.1002/wics.1375.

G. J. Szekely and M. L. Rizzo (2014).
Partial distance correlation with methods for dissimilarities,
Annals of Statistics, 42/6, 23822412.
article,
preprint.

C. D. Yenigun and M. L. Rizzo (2014).
Variable Selection in Regression using Maximal Correlation and
Distance Correlation,
Journal of Statistical Computation and Simulation.
March, 2014. DOI: 10.1080/00949655.2014.895354
 G. J. Szekely and M. L. Rizzo (2013).
Energy statistics: statistics based on distances.
Journal of Statistical Planning and Inference
Volume 143, Issue 8, August 2013, pp. 12491272.
DOI
 G. J. Szekely and M. L. Rizzo (2013).
The distance correlation ttest of independence in high dimension.
Journal of Multivariate Analysis, Volume 117, pp. 193213.
DOI
 G. J. Szekely and M. L. Rizzo (2012).
On the uniqueness of distance covariance.
Statistics & Probability Letters, Volume 82, Issue 12, 22782282.
DOI
 Maria L. Rizzo and Gabor J. Szekely (2010).
DISCO Analysis: A Nonparametric Extension of Analysis of Variance,
Annals of Applied Statistics Vol. 4, No. 2, 10341055.
Reprint
DOI
 Gabor J. Szekely and Maria L. Rizzo (2009). Brownian Distance
Covariance,
Annals of Applied Statistics,
Vol. 3, No. 4, 12361265.
Reprint
doi:10.1214/09AOAS312
 Gabor J. Szekely and Maria L. Rizzo (2009). Rejoinder: Brownian Distance.
Covariance, Annals of Applied Statistics, Vol. 3, No. 4, 13031308.
Reprint
doi:10.1214/09AOAS312REJ
 Maria. L. Rizzo (2009). New GoodnessofFit Tests for Pareto Distributions,
ASTIN Bulletin: Journal of the International Association of Actuaries,
39/2, 691715. PDF
 G. J. Szekely, M. L. Rizzo, and N. K. Bakirov (2007).
Measuring and Testing Independence by Correlation of Distances, Annals of Statistics,
Vol. 35 No. 6, pp. 27692794.
http://dx.doi.org/10.1214/009053607000000505.
Reprint

Bakirov, N. K., Rizzo, M. L., and Szekely, G. J. (2006).
A Multivariate Nonparametric Test of Independence, Journal of Multivariate Analysis
Volume 97, Issue 8 , September 2006, Pages 17421756
http://dx.doi.org/10.1016/j.jmva.2005.10.005.
 Szekely, G. J. and Rizzo, M. L. (2005) Hierarchical Clustering
via Joint BetweenWithin Distances: Extending Ward's Minimum Variance Method,
Journal of Classification, 22(2) 151183.
http://dx.doi.org/10.1007/s0035700500129.
 Szekely, G. J. and Rizzo, M. L. (2005) A New Test for
Multivariate Normality,
Journal of Multivariate Analysis,
93/1, 5880.
http://dx.doi.org/10.1016/j.jmva.2003.12.002.
Reprint
 Szekely, G. J. and Rizzo, M. L. (2004b) Mean Distance Test of Poisson Distribution,
Statistics and Probability Letters, 67/3, 241247
http://dx.doi.org/10.1016/j.spl.2004.01.005.
 Rizzo, M. L. (2003) Hierarchical Clustering Based on a Generalized
Measure of Homogeneity,
2003 Proceedings of the Joint Statistical Meetings, American Statistical
Association, Section for Physical and Engineering Sciences [CDROM],
Alexandria, VA: American Statistical Association.
 Szekely, G. J. and Rizzo, M. L. (2004) Testing for Equal
Distributions in High Dimension, InterStat, Nov. (5).
Reprint
 M. L. Rizzo (2005) Minimum Energy Clustering
Proceedings of Interface/Classification Society of North America,
Joint Annual Meeting, 2005.
 Rizzo, M. L. (2002a). A Test of Homogeneity for Two Multivariate Populations,
2002 Proceedings of the American Statistical Association, Physical and Engineering
Sciences Section [CDROM], Alexandria, VA: American Statistical Association.
 Rizzo, M. L. (2002b). A New Rotation Invariant GoodnessofFit Test,
Ph.D. dissertation, Bowling Green State University.
Abstract
 Szekely, G. J. (2002) Estatistics: the Energy of Statistical Samples,
Technical Report No. 0216, Bowling Green State University, Department
of Mathematics and Statistics, October 2002. PDF
 Szekely, G. J. (2000) Estatistics: Energy of
Statistical Samples, Bowling Green State University, Department of
Mathematics and Statistics Technical Report No. 0305.
 Szekely, G. J. (1989) Potential and Kinetic Energy in Statistics,
Lecture Notes, Budapest Institute of Technology (Technical University).
R is a free software environment
for statistical computing and graphics, available at the
Comprehensive R
Archive Network (CRAN)..
This software is distributed under
GNU General
Public License Version 2, or later. See
COPYING for the license.
Questions or comments on software: Maria Rizzo, email address above
[go to References]
MATLAB:
Some functions in energy have been translated to Matlab.