Index Catalog // ScholarsArchive@OSU

Creator:: James, Addison
Abstract:: Nonparametric model-assisted estimators have been proposed to improve estimates of finite population parameters. More efficient estimators are obtained when the parametric model is misspecified due to the flexibility of nonparametric models. In this dissertation, we derive information criteria to select appropriate auxiliary variables to use in an additive model-assisted method....
Resource Type:: Dissertation

Creator:: Wang, Lu
Abstract:: Monotone additive models are useful in estimating productivity curves or analyzing disease risk where the predictors are known to have monotonic effects on the response. Existing literature mainly focuses on univariate monotone smoothing. Available methods for the estimation of monotone additive models are either difficult to interpret or have no...
Resource Type:: Dissertation

Creator:: Payton, Quinn
Abstract:: Density dependence is an ecological concept concerning the mechanisms of change in the size of a population. The inability to census ecological populations confounds approaches to identify and quantify the level of density dependence. Statistical tests which ignore the presence of measurement error tend to result in misspeci fied type...
Resource Type:: Dissertation

Creator:: Derryberry, DeWayne R.
Abstract:: The semi-parametric approach to the analysis of proportional hazards survival data is relatively new, having been initiated in 1972 by Sir David Cox, who restricted its use to hypothesis tests and confidence intervals for fixed effects in a regression setting. Practitioners have begun to diversify applications of this model, constructing...
Resource Type:: Dissertation

Creator:: Suh, Eun-Young
Abstract:: Semiparametric maximum likelihood analysis allows inference in errors-invariables models with small loss of efficiency relative to full likelihood analysis but with significantly weakened assumptions. In addition, since no distributional assumptions are made for the nuisance parameters, the analysis more nearly parallels that for usual regression. These highly desirable features and...
Resource Type:: Dissertation

Creator:: Yao, Feng
Abstract:: This dissertation contains three essays on nonprametric and semiparametric regression mod- In the first essay, we propose an estimation procedure for value at risk (VaR) and expected shortfall (TailVaR.) for conditional distributions of a time series of returns on a financial asset. Our approach combines a local polynomial estimator of...
Resource Type:: Dissertation

Creator:: Yang, Ke
Abstract:: This dissertation is composed of three essays regarding the finite sample properties of estimators for nonparametric models. In the first essay we investigate the finite sample performances of four estimators for additive nonparametric regression models - the backfitting B-estimator, the marginal integration M-estimator and two versions of a two stage...
Resource Type:: Dissertation

ScholarsArchive@OSU