|Active Set Adaptive Sampling 1
Steven K. Tompson 2
Pennsylvania State University
Los Alamos National Laboratory
Monday, 19 April 2004
E202 Engineering Building
This seminar will describe adaptive sampling designs in which, at any point
in the sampling, the next unit or set of units is with high probability
selected from a distribution that depends on the values of variables of
interest in an active set of units already selected. With lower probability,
the next selection is made from a distribution not dependent on those
values. The active set may consist of the entire current sample, or only the
most recently selected unit, or a wide range of other possibilities.
Design-unbiased estimation with such designs is based on a combination of
initial and conditional selection probabilities, and these preliminary
estimators are improved using the Rao-Blackwell method. Markov chain
resampling estimators are used for larger sample sizes. Network and
spatially-based applications of the designs to a hidden human population at
risk for HIV/AIDS and a wintering waterfowl survey are evaluated. The new
designs can give efficiency gains over comparable conventional designs in
some situations and, in comparison with other adaptive and link-tracing
sampling methods, the present class of strategies has advantages in
flexibility regarding adaptive criteria and breadth and depth of sample
coverage, ease of implementation, control of sample sizes, and the
availability of robust if computationally intense design-based estimators.
Key words: Adaptive sampling, link-tracing designs, Markov chain Monte
Carlo, network sampling, Rao-Blackwell, spatial sampling.
1 Los Alamos National Laboratory Paper LA-UR-04-0852
2 Department of Statistics, 314 Thomas Building, Pennsylvania State
University, University Park, PA 16801 USA. Current address: Statistical
Sciences Group, D-1, MS F-600, Los Alamos National Laboratory, Los Alamos,
NM 87544, email@example.com.
Partial support for this work has been provided
by the National Center for Health Statistics. The Statistical Sciences Group
of Los Alamos National Laboratory provided time and resources for this work
through their Visiting Faculty Program.
Refreshments will be served at 3:45 p.m. in Room 008 of the Statistics