2021 ADC – Databases as Statistical Backend Computing

Professor Thomas Lumley, The University of Auckland

Abstract:

Statistical estimation and inference tends to combine simple matrix or table operations on large data sets and complex, task-specific calculation on small summaries extracted from these operations. This division of labour matches the division between flexible but inefficient statistical programming environments and modern database systems. I will discuss the use of R and lazy data backends to combine rapid prototyping, flexible programming, and the ability to use large data sets. I will also talk about the use of statistical sampling theory to further reduce the computational burden.

Biography: 

Thomas Lumley is Professor of Biostatistics in the Statistics department at the University of Auckland. He obtained his PhD in Biostatistics at the University of Washington, Seattle. He has wide-ranging research interests in theoretical and applied biostatistics and statistical computing, recently including large-scale genomics and estimation based on subsamples of large data sets. Thomas is a Fellow of the Royal Society of New Zealand and the American Statistical Association, and has been an R Core developer since 1997.

Date

Feb 01 2021
Expired!

Time

3:45 pm - 4:45 pm

Local Time

  • Timezone: America/New_York
  • Date: Jan 31 2021
  • Time: 9:45 pm - 10:45 pm