B.S., Princeton University
Ph.D., Yale University
Timothy G. Gregoire’s research is directed to the application and development of statistical methods for natural resources and environmental phenomena. One longstanding focus has been on probability sampling techniques, a second focus has been on statistical modeling of longitudinal and spatially correlated data, and a third has been an abiding interest on the nature of statistical inference. Recent pursuits include the design, planning and implementation of the national forest inventory for the Kingdom of Bhutan; development of aboveground biomass prediction models for major tree species of Bhutan; reduced impact logging in tropical forests of Democratic Republic of Congo; application of line intersect sampling for coarse woody debris biomass estimation in Brazilian forests; assessing the effects of spatial autocorrelation in remote sensing with systematic sampling; good practice on reporting data quality for land cover surveys, in collaboration with colleagues at UN FAO (Rome); and wood density estimation in highly diverse tropical forests.