The Canadian Journal of Statistics Award 2018

Victor de Oliveira
Benjamin Kedem
The Canadian Journal of Statistics Award
“Bayesian analysis of a density ratio model.” (Volume 45, no. 3, pp. 274-289)


The Canadian Journal of Statistics Award is presented each year by the Statistical Society of Canada to the author(s) of an article published in the journal, in recognition of the outstanding quality of the methodological innovation and presentation.


This year’s winner is the article entitled “Bayesian analysis of a density ratio model.” (Volume 45, no. 3, pp. 274-289) by V. de Oliveira and B. Kedem.

The paper proposes a Bayesian approach for the analysis of a semiparametric density ratio model, a model useful for the integration of data from multiple sources.  The proposed Bayesian analysis uses a non-parametric likelihood and a transformed Gaussian prior for the “non-parametric part” of the model that guarantees the validity of the Bayesian analysis. The model is illustrated with the analysis of motor vibration data obtained from three different locations on a motor. The committee noted that the paper contains a novel application of the Metropolis-Hastings algorithm to fit a complex model; it was innovative and the presentation was of very high quality. 

Victor de Oliveira is a Professor in the Department of Management Science and Statistics at the University of Texas at San Antonio (UT--San Antonio). He holds a PhD in Statistics from the University of Maryland--College Park and a MS. in Water Resources from Simon Bolivar University (Venezuela). He was a faculty member at Simon Bolivar University and the University of Arkansas (USA) before joining UT--San Antonio in 2006. His main research area is spatial statistics, with emphasis on geostatistical methods, and more recently he is working on semiparametric modeling. He received the Distinguished Achievement Award from the American Statistical Association Section on Statistics and the Environment, and is an elected member of the International Statistical Institute.

Benjamin Kedem is a Professor, Department of Mathematics, and an affiliate of the Institute for Systems Research, University of Maryland. He received his PhD in statistics from Carnegie-Mellon University in 1973. His research is summarized in the books Time Series Analysis by Higher Order Crossings, IEEE Press, 1994; Regression Models for Time Series Analysis, Wiley, 2002 (with Kostantinos Fokianos); and Statistical Data Fusion, World Scientific, 2017 (with Victor De Oliveira and Michael Sverchkov). He is the recipient of several awards including the IEEE W.R.G. Baker Award, IBM Faculty Award, and NASA Award in connection with the Tropical Rainfall Measuring Mission. He is an ASA Fellow.

Benjamin Kedem will present an overview of their work in a special session at this year’s SSC Annual Meeting at McGill University.

The citation for the award reads: 

The article entitled “Bayesian analysis of a density ratio model” by Victor de Oliveira and Benjamin Kedem is recognized for creativity and excellence in presentation.


Thanks to Louis-Paul Rivest, who was primarily responsible for producing this material.