The objective of this dissertation is to develop a suitable statistical methodologyfor functional data analysis. Modern advanced technology allows researchers to collectsamples as functional which means the ideal unit of samples is a curve. We considereach functional observation as the resulting...

Semi-parametric and nonparametric modeling and inference have been widely studied duringthe last two decades. In this manuscript, we do statistical inference based on semi-parametricand nonparametric models in several different scenarios.Firstly, we develop a semi-parametric additivity test for...

Zero-inflated data abound in ecological studies as well as in other scientific and quantitative fields. Nonparametric regression with zero-inflated response may be studied via the zero-inflated generalized additive model (ZIGAM). ZIGAM assumes that the conditional distribution of the response...

Generalized autoregressive conditional heteroscedasticity (GARCH) models are widely used in financial markets. Parameters of GARCH models are usually estimated by the quasi-maximum likelihood estimator (QMLE). In recent years, economic theory often implies equilibrium between the levels of time...

We study a special class of misspecified generalized linear models, where the true model is a mixed effect model but the working model is a fixed effect model with parameters of dimension increasing with sample size. We provide a sufficient condition both in linear models and generalized linear...