Statistical Engineering Division, ITL, NIST
Tuesday, Oct. 17, 2023, 1:00-2:00 PM ET (11:00 AM-12:00 PM MT)
In person at: Gaithersburg Bldg. 101 LR D with VTC to Boulder 1-4072
Online at: https://bluejeans.com/419684224/0300
Add this talk to your calendar: https://inet.nist.gov/calendar/ics/2264786
Abstract: The NIST inter-laboratory studies involve combining heterogeneous data from different laboratories with the laboratories reporting uncertainties that are often unreliable or missing. The talk explores the possibility of discarding these uncertainties by introducing new procedures to estimate the common mean on the basis of remarkable discrete (random) distribution. The mathematical implications of this setting involve so called self-dual orthogonal polynomials, non-traditional limit theorems for sums of dependent random variables and new formulas for the Gauss hypergeometric function.
Bio: Andrew Rukhin got his M.S. in Mathematics (Honors) from the Leningrad State University (Russia) in 1967. In 1970 he defended his Ph.D. Thesis in Statistics at the Steklov Mathematical Institute. After emigrating from the USSR Andrew Rukhin taught at Purdue University (1977-1987) at University of Massachusetts, Amherst (1987-1989), and University of Maryland at Baltimore County (1987-2008). In 1994 he was appointed Mathematical Statistician in the Statistical Engineering Division, the National Institute of Standards and Technology where he works now. He is engaged in applied statistical research in Inter-laboratory Studies, Testing of Randomness, Bayesian Statistics, and Research Synthesis. Andrew is a Fellow of the Institute of Mathematical Statistics, and a Fellow of the American Statistical Association. He won Senior Distinguished Scientist Award By Alexander von Humboldt-Foundation (1990) and was awarded the Youden Prize for Inter-laboratory Studies three times (1998, 2007, 2018).
Host: Adam Pintar
Note: This talk will be recorded to provide access to NIST staff and associates who could not be present to the time of the seminar. The recording will be made available in the Math channel on NISTube, which is accessible only on the NIST internal network. This recording could be released to the public through a Freedom of Information Act (FOIA) request. Do not discuss or visually present any sensitive (CUI/PII/BII) material. Ensure that no inappropriate material or any minors are contained within the background of any recording. (To facilitate this, we request that cameras of attendees are muted except when asking questions.)
Note: Visitors from outside NIST must contact Lochi Orr at least 24 hours in advance.