Theses Doctoral

Efficient Estimation of the Expectation of a Latent Variable in the Presence of Subject-Specific Ancillaries

Mittel, Louis Buchalter

Latent variables are often included in a model in order to capture the diversity among subjects in a population. Sometimes the distribution of these latent variables are of principle interest. In studies where sequences of observations are taken from subjects, ancillary variables, such as the number of observations provided by each subject, usually also vary between subjects. The goal here is to understand efficient estimation of the expectation of the latent variable in the presence of these subject-specific ancillaries.
Unbiased estimation and efficient estimation of the expectation of the latent parameter depend on the dependence structure of these three subject-specific components: latent variable, sequence of observations, and ancillary. This dissertation considers estimation under two dependence configurations. In Chapter 3, efficiency is studied under the model in which no assumptions are made about the joint distribution of the latent variable and the subject-specific ancillary. Chapter 4 treats the setting where the ancillary variable and the latent variable are independent.

Files

  • thumnail for Mittel_columbia_0054D_14284.pdf Mittel_columbia_0054D_14284.pdf application/pdf 572 KB Download File

More About This Work

Academic Units
Statistics
Thesis Advisors
Rabinowitz, Daniel
Degree
Ph.D., Columbia University
Published Here
October 20, 2017