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The University of New Mexico

Statistics Research

Statistics
Statistics

Professor Christensen's research interests are in models that employ linear mean structures and in Bayesian methodology.  He contends that this includes virtually all of statistics. 

 

Statistics

My research focuses on statistical applications in genetics and evolutionary biology. Particular areas have included coalescent theory and its applications, phylogenetics, and human genetics.

Statistics
Statistics
A theme of my research is the development of statistical models motivated by real-world problems to reveal scientifically meaningful structure in multivariate data by decomposing a mixture into its constituent sources. Method development is based on parsimonious models which can extend to uncover more complicated structure in the data. This strategy allows a researcher to either address elemental, pre-specified scientific questions or reveal more complicated structure given enough evidence. Two areas of application are in estimating animal diets in ecological foodwebs and in using functional imaging of the human brain to estimate how connections between brain regions differ between patient populations. Implications include better evidence-based decisions for environmental management and improved understanding of mental differences and treatment.

(updated 20160107)

Statistics

My research concentrates on survey sampling, mixed models and nonparametric regression. Much of my work develops new statistical theory and methods in those three areas. I am interested in regression coefficient estimation, partially linear models, lack of fit tests and identification of influential observations in dual frame surveys. My interests also include nonparametric regression for complex surveys, generalized linear mixed models and mixed random forests.

Statistics
Statistics

My primary research interests are in statistical computing, nonparametric function estimation, data mining, time series and mixed models. I am interested in developing new statistical theory and methods and in applying statistical tools to real life problems.