Health Sciences Administration

Health Sciences Administration

A spatio-temporal model is constructed for interpolation of yearly precipitation data from 1982 to 1996 over the African Sahel. The precipitation data used in the analysis comes from the Global Historical Climatology Network. The spatio-temporal model is based on a Gaussian Markov random field (GMRF) with AR(1)-dependence in time and a spatial component modeled using a GMRF that approximates a stationary field with Matern covariance.

Advisor: Raphael Gottardo and Mathias Drton

Advisors: Raphael Gottardo & Mathias Drton

Abstract:

Bulk gene expression experiments utilizing large populations of cells can accurately determine the average population state, but to study cell-to-cell variation it is logical to repeatedly sample single cells. Advances in microfluidics are now enabling the expression profile of thousands of genes to be measured in individual cells.

Advisor: Jon Wakefield Abstract: Area and time-specific estimates of disease rates, cause-specific mortality rates and other key health indicators are of great interest for health care and policy purposes. Such estimates provide the information needed to identify areas with increased risk, effectively allocate resources, and target interventions. A wide variety of data, such as vital statistics, complex surveys, demographic surveillance sites, and disease registries, are used for these purposes.