Thu 3rd September 2015

Two Upcoming Lectures by van Eeden Invited Speaker Professor Roger Cooke

Coming up in September, the Statistics Department will be hosting two lectures by van Eeden invited lecturer
 Professor Roger Cooke (Chauncey Starr Chair for Risk Analysis, Resources for the Future, USA; and Department of Mathematics,
Technische Universiteit Delft, Netherlands).

The lectures will be on Tuesday, September 22nd and on Thursday, September 24th. There will be small receptions before 
each lecture in the lobby of the building where the lecture is being held. Lecture times, locations, and abstracts are below. 

Date:  Tuesday, September 22
Time:  11am - 12pm
Location:  Lecture Theatre 102, Michael Smith Labs (2185 East Mall)
Title:  Vine Regression
Abstract:  Vine regression is a parametric non-linear method that does not rely
on the Gaussian error assumption. Regression is considered as conditional
expectation after fitting a multivariate distribution.

Regular Vine theory provides a rich class of N-dimensional densities with
arbitrary one-dimensional margins and arbitrary N-choose-2 (conditional)
bivariate copulas. For ordinal data, "Gaussian smoothing" uses regular
vines to build a tractable density that emulates the empirical rank
correlation structure. Conditional expectations and variances can be
computed in the emulating density. The effect of a given regressor on
a variable of interest is computed as the expected difference of two
regression functions, where (a) the regression is conditional on all
regressors, and (b) the regression is conditional on all regressors
with the given regressor augmented by one unit. In one stroke this
eliminates issues like confounders, interactions, collinearity,
transformations, heteroscedasticity, marginality etc.

Vine regression is illustrated by computing the effect of duration of
breast feeding on IQ using the National Longitudinal Study of Youth. The
talk will give a brief introduction to copulas and vines.


Date:  Thursday, September 24, 2015
Time:  4pm - 5pm
Location:  Room 4192, Earth Sciences Building (2207 Main Mall)
Title:  Structured Expert Judgment and Invasive Species in the Great Lakes
Abstract:  Structured Expert Judgment (SEJ) treats experts as statistical
hypotheses. Experts quantify their uncertainty for variables from
the field for which true values are known post hoc, in addition to the
variables of interest. Statistical accuracy and informativeness scores are
used to construct "performance based combinations", which in turn can be
evaluated and compared with other combinations schemes.  Many examples
of SEJ are in the TU Delft expert judgment data base.

SEJ has recently been employed to assess the impact of an Asian Carp
invasion into Lake Erie. A general introduction to SEJ, including in-
and out-of-sample validation will be given, followed by an in depth
discussion of the Erie application.

A reference for expert judgment is the following book.
Cooke R. (1991),  Experts in Uncertainty; Opinion and Subjective Probability 
in Science, Oxford University Press; ISBN 0-19-506465-8.

a place of mind, The University of British Columbia

Department of Statistics

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Fax: 604.822.6960

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