The Department of Statistics at Texas A&M University, one of the premier statistics departments in the world, offers quality online statistics degree and certificate programs. This online statistics program is an integrated extension of the renowned on-campus program at Texas A&M University. It provides the same instruction, course materials, and exams - with the flexibility to fit your schedule. We offer a 36 hour non-thesis Masters of Science in Statistics program and also a 12 hour Certificate program. We can also provide individual Statistics courses.
Texas A&M statistician Ray Carroll and his legion of protégés have made fundamental contributions to many areas of statistical research. As the inaugural holder of the Jill and Stuart A. Harlin '83 Chair in Statistics, Carroll hopes to apply his varied and pioneering expertise to help improve vascular care, Dr. Harlin's medical specialty.Read More →
11:30 AM / 12:30 PM Blocker Building (BLOC) Room 113 979-845-3141
Laboratory of Interdisciplinary Statistical Analysis (LISA)
Virginia Tech, Department of Statistics
"LISA 2020: Creating a Network of Statistical Collaboration Laboratories"
To increase the global impact of statistics and make the profession more useful for solving real-world problems, LISA—The Laboratory for Interdisciplinary Statistical Analysis at Virginia Tech—is partnering with universities and individuals around the world to create a network of 20 new statistical collaboration laboratories in developing countries by 2020.
LISA and its partners will educate and train statisticians from developing countries to communicate and collaborate with non-statisticians and then support these statisticians to create statistical collaboration laboratories in their home countries to help researchers, government officials, local industries, and NGOs apply statistical thinking and data science to make better decisions through data. At LISA and elsewhere, we will unlock the collaborative potential of technically sound statisticians who will in turn unlock the research potential of their collaborators and teach other statisticians to do the same. These local research collaborations, now with the power of statistical thinking and data science open to them, will be key to improving human welfare worldwide.
This talk will focus on the steps of this program, called “LISA 2020”, including how LISA trains statisticians to become interdisciplinary collaborators, how statistical collaboration laboratories create knowledge and serve the mission of land grant universities, and how the LISA 2020 mentoring network we are building will assist statisticians in developing countries to enable and accelerate research.
11:30 AM / 12:30 PM Blocker Building (BLOC), Room 113 979-845-3141
Department of Mathematical Sciences
University of Texas at Dallas
"Simultaneous Inference for the Mean of Functional Time Series"
For functional time series with physical dependence, we construct confidence bands for its mean function. The physical dependence is a general dependence frame, and it slightly relaxes the conditions of m-approximable dependence. We estimate functional time series mean functions via spline smoothing technique. Confidence bands have been constructed based on a long-run variance decomposition and a strong approximation, which are satisfied under mild regularity conditions. Simulation experiments provide strong evidence that corroborates the asymptotic theories. Additionally, an application to S&P 500 index data demonstrates a non-constant volatility mean function at a certain significance level.
Keywords: confidence bands, functional time series, high-frequency data, long-run variance, nonparametric regression, spline.
Joint work with Ming Chen.