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X-ORIGINAL-URL:http://acsw.core.edu.au/
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UID:MEC-d2a2c1da2acde3ed27003dba9c3c1ccc@acsw.core.edu.au
DTSTART:20210201T044500Z
DTEND:20210201T054500Z
DTSTAMP:20210115T011300Z
CREATED:20210115
LAST-MODIFIED:20210119
SUMMARY:2021 ADC – Databases as Statistical Backend Computing
DESCRIPTION:Professor Thomas Lumley, The University of Auckland\nAbstract:\nStatistical 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.\nBiography: \nThomas 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.\n
URL:http://acsw.core.edu.au/events/2021-adc-keynote-presentation-thomas-lumley
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