Events

Filter by:

Limit to events where the title matches:
Limit to events where the first date of the event:
Date range
Limit to events where the first date of the event:
Limit to events where the type is one or more of:
Limit to events tagged with one or more of:
Limit to events where the audience is one or more of:
Friday, September 13, 2013 2:30 pm - 2:30 pm EDT (GMT -04:00)

David Sprott Distinguished Lecture by Jerome Friedman

Sparsity, boosting and ensemble methods

Jerome FriedmanStatistical or machine learning involves predicting future outcomes from past observations. Many present day applications involve large numbers of predictor variables, sometimes much larger than the number of cases or observations available to train the learning algorithm. In such situations traditional statistical methods fail.

Tuesday, November 26, 2013 4:00 pm - 4:00 pm EST (GMT -05:00)

WatRISQ seminar by Steven Kou, National University of Singapore

Robust measurement of economic tail risk

We prove that the only tail risk measure that satisfies a set of economic axioms proposed by Schmeidler (1989, Econometrica) and a statistical requirement called elicitability (i.e. there exists an objective function such that a reasonable estimator must be a solution of minimizing the expected objective function) is the median shortfall, which is the median of the tail loss distribution and is also the VaR at a high confidence level.

Wednesday, May 14, 2014 4:00 pm - 4:00 pm EDT (GMT -04:00)

David Sprott Distinguished Lecture by Art B. Owen

Empirical likelihood

Art OwenLikelihood methods provide one of the most versatile and effective ways to handle data. They give us tests and confidence intervals with very strong optimality measures. But the cost for using them is usually that we have to know a family of distributions generating our data.

Thursday, September 25, 2014 2:30 pm - 2:30 pm EDT (GMT -04:00)

David Sprott Distinguished Lecture by Eduardo S. Schwartz

The real options approach to valuation: challenges and opportunities

Eduardo SchwartzThis lecture provides an overview of the real options approach to valuation mainly from the point of view of the author who has worked in this area for over 30 years. After a general introduction to the subject, numerical procedures to value real options are discussed.

Thursday, May 14, 2015 4:00 pm - 4:00 pm EDT (GMT -04:00)

David Sprott distinguished lecture by William Woodall, Virginia Tech

Monitoring and Improving Surgical Quality

Some statistical issues related to the monitoring of surgical quality will be reviewed in this presentation. The important role of risk-adjustment in healthcare, used to account for variations in the condition of patients, will be described. Some of the methods for monitoring quality over time, including a new one, will be outlined and illustrated with examples.

Thursday, September 24, 2015 4:00 pm - 4:00 pm EDT (GMT -04:00)

David Sprott distinguished lecture by Raymond J. Carroll, Texas A&M University

Constrained maximum likelihood estimation for model calibration using summary-level information from external big data sources.

Carroll PosterInformation from various public and private data sources of extremely large sample

Some new phenomena in high-dimensional statistics and optimization

Statistical models in which the ambient dimension is of the same order
or larger than the sample size arise frequently in different areas of
science and engineering.  Examples include sparse regression in
genomics; graph selection in social network analysis; and low-rank
matrix estimation in video segmentation.  Although high-dimensional
models of this type date back to seminal work of Kolmogorov and