Throughout my research career, I have developed links between statistics and the life sciences. I regard this "bridge building" as the main motivation of my research work. I first became aware of the potential value of applying efficient and valid statistical methodology to the agricultural and e...
Throughout my research career, I have developed links between statistics and the life sciences. I regard this "bridge building" as the main motivation of my research work. I first became aware of the potential value of applying efficient and valid statistical methodology to the agricultural and environmental sciences during my doctoral studies in mathematics. This interest stimulated me to work to develop statistical models appropriate to ecology during my post-doctoral fellowship. I have continued to elaborate, expand and assess statistical models and methods of data analysis since I joined the faculty of McGill. My D.Sc. thesis project was in temporal statistics, my post-doctoral fellowship has been in spatial statistics, and my research work in applied statistics at McGill incorporates both components.
The fields of application are agricultural, biological and environmental sciences, with animal, earth and plant sciences, chronobiology and dendrochronology, forest ecology and limnology, quantitative genetics and wood technology as subfields of application. Key words are autocorrelation, complexity, heterogeneity, heteroscedasticity, nonstationarity, periodicity, scale, and structure.