Richard Lockhart, Professor
Department of Statistics and Actuarial Science
|Phone: (778) 782 3264 | Messages: (778) 782 3803 | Fax: (778) 782 4368
Office: K 10561 | Email: lockhart (at) sfu (dot) ca
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Cambridge Mini-course, Lent, 2017
Course Notes, 8 Mar
Inference for High Dimensional Regression
Lecture Slides -
Big Data Workshop at SFU
PIMS page
Statistical Inference for Large Scale Data
Program, abstracts -
Big Data Workshop at UBC
PIMS page
Big Data in Environmental Science
Program, abstracts -
Statistics Canada
The Daily -
United States Census Bureau
Data -
UK Statistics
StatsUserNet -
Putnam solutions
1985 1986 1987 1988 1989 -
The Statistical Society of Canada
Home -
Physics and Statistics at BIRS
July 2010 Workshop -
My old home page
I used to have a simpler page -
SFU sites
My department
My university
High Dimensional Inference
Lately I have had the privilege of working with Jon Taylor, Ryan Tibshirani, and Rob Tibshirani on inference for LASSO and LARS. They are experts; I am a joy-rider. Too many co-authors to put pictures at left. Instead: Stanford.
Methodology in Goodness of Fit
I do goodness of fit, developing testing methods and associated large sample theory largely with Michael Stephens, Federico O'Reilly, Alberto Contreras Cristan, and a number of former students. Ted Anderson is at left.
Directional data
I have written a number of papers on directional data with Michael Stephens and Peter Guttorp. With Michael I wrote about goodness-of-fit for the von~Mises distribution and worked with a student on von~Mises mixtures. With Peter I worked on direction finding for downed aircraft. That paper does Bayesian analysis of the problem of finding and object on the basis of bearings taken with von~Mises distributed errors. It also considers ``outlier'' detection in a directional context. Michael's PhD supervisor, Geoff Watson, is pictured at left.
Large Sample Theory
I like to work on large sample theory with what I think of as clean, simple conditions. Peter Guttorp and I did this sort of thing in work on inference in irregularly sampled random walks. That work was motivated by a paper I wrote applying the local central limit theorem to prove that on an explosive trajectory of a Bienaymé-Galton-Watson only the mean, variance and perhaps one other arithmetic parameter admit consistent estimates. Then Peter and I worked on the large sample behaviour of quadratic forms in uniform order statistics. That grew out of work on Q-Q plots some of which I did with Graham McLaren. Recently I proved a conditional limit theorem for empirical distribution functionl tests. At left is Sir Francis Galton.
Applied papers
I have a paper with Peter Guttorp about finding downed aircraft, work with Chandanie Perera on thermoluminescence dating, early work with (or really for -- I was a summer student at the time having just finished my BSc) Jim Zidek on traffic loading on the Lion's Gate Bridge.