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Claudio Fuentes sitting in office space

Claudio Fuentes

Associate Professor
Department of Statistics
Adjunct, College of Public Health and Human Sciences

Claudio Fuentes

Associate Professor
Department of Statistics
Adjunct, College of Public Health and Human Sciences

Research interests

  • Clustering and Classification Problems
  • Post-selection Inference
  • Bayesian Methods
  • Applied Statistics

Instructional activities

  • ST 651 Linear Model Theory I (Winter 2014, 2016)
  • ST 652 Linear Model Theory II (Spring 2016)
  • ST 562 Theory of Statistics II (Winter 2015, 2017)
  • ST 552 Statistical Methods II (Winter 2012, 2013, 2014)
  • ST 443/543 Applied Stochastic Models (Spring 2017)
  • ST 422/522 Introduction to Mathematical Statistics II (Winter 2017)
  • ST 412/512 Methods of Data Analysis II (Spring 2013, 2014, 2015, 2017; Winter 2016)
  • ST 314 Introduction to Statistics for Engineers (Spring 2012, 2013, 2014, 2015, 2016)

Professional societies

  • American Statistical Association (ASA)
    • President of the Oregon Chapter 2016-2017
  • Institute of Mathematical Statistics (IMS)
  • International Society for Bayesian Analysis (ISBA)
  • Western North American Region of the International Biometric Society (WNAR)

Education

Ph.D. Statistics, University of Florida, Gainesville, 2011

M.S. Statistics, University of Florida, Gainesville, 2008

M.S. Statistics, Pontifical Catholic University of Chile, 2003

B.S. Mathematics, Pontifical Catholic University of Chile, 2001

Publications

  • Fuentes, C., Casella, G., and Wells, M.T (2018), “Confidence Intervals for the Means of the Selected Populations,” Electronic Journal of Statistics, 12 (1), pp. 58-79.
  • León-Novelo, L., Fuentes, C., and Emerson, S. C. (2017), “Marginal Likelihood Estimation of Negative Binomial Parameters with Applications to RNA-Seq Data,” Biostatistics, 18 (4), pp. 58-79.
  • De la Cruz, R., Fuentes, C., Meza, C., Lee, D. J., and Arribas-Gil, A. (2017), “Predicting Pregnancy Outcomes Using Longitudinal Information: A P-Splines Mixed-Effects Model Approach,” Statistics in Medicine, 36 (13), pp. 2120-2134.
  • Gopal, V., Fuentes, C., and Casella, G. (2012), “bayesclust: An R package for Testing and Searching for Significant Clusters,” Journal of Statistical Software, 47 (14), pp. 1-21.
  • Fuentes, C., and Casella, G. (2009), “Testing for the Existence of Clusters” (with discussions), Statistics and Operations Research Transactions (SORT), 33 (2), pp. 115-158.