Search results
-
-
Title
-
Analysis of failure time data with missing and informative auxiliary covariates.
-
Author
-
Ghosh, Lipika
-
Date Created
-
2011
-
Subjects--Topical
-
Statistics, Mathematics, Biometry
-
Description
-
In this dissertation we use Cox's regression model to failure time data with continuous informative auxiliary variables in the presence of a validation subsample. The work is motivated by a common problem of missing or mismeasured covariates in su...
-
-
Title
-
Independent Screening for Nonparametric Additive Cox Model
-
Author
-
Yu, Sha
-
Date Created
-
2020
-
Subjects--Topical
-
Statistics
-
Description
-
Survival data with ultrahigh dimensional covariates are increasingly common recently due to the rapid development in technologies. It is challenging to model them using survival models in order to understand the association between covariate infor...
-
-
Title
-
Interval Estimation for Semiparametric Predictive Regression
-
Author
-
Hong, Shaoxin
-
Date Created
-
2018
-
Subjects--Topical
-
Statistics
-
Description
-
Predictive regression is an important research topic in financial econometrics. Various estimation methods have been proposed for it, but they suffer from complicated asymptotic limits which depend on whether or not the predicting variable is stat...
-
-
Title
-
Modeling Vector Time Series Data
-
Author
-
Liu, Yi
-
Date Created
-
2013
-
Subjects--Topical
-
Statistics
-
Description
-
ABSTRACTIn this dissertation, firstly, I study spatial quantile regression estimation of multivariate threshold time series models. Asymptotic normality of the proposed spatial quantile regression estimator is established. Simulations and a real e...
-
-
Title
-
NONPARAMETRIC PREDICTIVE REGRESSION
-
Author
-
Yu, Xintian
-
Date Created
-
2016
-
Subjects--Topical
-
Statistics, Finance, Economics
-
Description
-
In financial time series nonlinear effects and time-varying effects are observed. In this dissertation we propose a predictive regression model with time varying coefficients and functional coefficients. It allows for nonstationary predictors. We establi...
-
-
Title
-
Non-nested Model Selection via Empirical Likelihood
-
Author
-
Zhao, Cong
-
Date Created
-
2017
-
Subjects--Topical
-
Statistics
-
Description
-
In this dissertation we propose an empirical likelihood ratio (ELR) test to conductnon-nested model selection. It allows for heteroscedasticity and works for any twosupervised statistical learning methods under mild conditions. We establish asympt...
-
-
Title
-
ROBUST GENERALIZED LIKELIHOOD RATIO TEST BASED ON PENALIZATION
-
Author
-
Zhang, Meijiao
-
Date Created
-
2018
-
Subjects--Topical
-
Statistics
-
Description
-
The Least absolute deviation combined with the Least absolute shrinkage andselection operator (LAD-LASSO) estimator can do regression shrinkage and selectionand is also resistant to outliers or heavy-tailed errors which is proposed in Wang etal. (...
-
-
Title
-
TESTING PREDICTABILITY OF ASSET RETURNS
-
Author
-
Wu, Li
-
Date Created
-
2014
-
Subjects--Topical
-
Statistics, Finance
-
Description
-
In this paper, a L2 type nonparametric test is developed to test a specific nonlinear parametric regression model with near-integrated regressors. The asymptotic distributions of the proposed test statistic under both null and alternative hypothes...
-
-
Title
-
Unifying Estimation of Varying-coefficient Models
-
Author
-
yin, weitong
-
Date Created
-
2019
-
Subjects--Topical
-
Statistics
-
Description
-
Varying-coefficient models are widely used to analyze the relationship between a response and a group of covariates. Existing research shows different convergence rates for the estimators of coefficient for the stationary part and the nonstationar...