An Approach to Semiparametric Regression with Random Covariates

ISR-affiliated Professor Ben Kedem (Math) has received a three-year, $100K NSF grant for An Approach to Semiparametric Regression with Random Covariates. Given multiple multivariate data sources, each represented by an unknown multivariate distribution, the investigator proposes an approach to regression analysis based on relationships between semiparametric estimates of these multivariate distributions. Resulting from this are regression estimates expressed as estimates of the conditional expectation of a response given its covariates, for each source. The investigator plans to study the statistical properties of the regression estimates, associated diagnostic tools, the applicability and computability of the method using real data, and compare the method to multiple and kernel regression methods.