Space-time panel data widely exist in many research fields such as economics, management, geography and environmental science. It is of interest to study the relationship between response variable regressors which come from above by establishing regression models. This paper introduces a new fixed effects partially linear varying coefficient model with nonseparable space-time filters. On basis ...

ii c 2013 Yi Liu ALL RIGHTS RESERVED iii ABSTRACT YI LIU. Generalized Quasi-Likelihood Ratio Statistics for Multivariate Time-varying Coefficient Regression Models. (Under the direction of DR. JIANCHENG JIANG) Generalized likelihood ratio statistics have been a generally applicable method for testing nonparametric hypotheses about nonparametric functions.It has been widely used in many research...

This paper extends the partially linear varying coefficient model to contain time trend and nonstationary variables as regressors. We use the profile likelihood method to estimate both time trend coefficient in the linear component and the functional coefficients in the nonlinear component and establish their asymptotic distributions. Monte Carlo simulations are shown to investigate the finite ...

234 Abstract—Currently whole world is facing the problem of energy disaster. So to overcome this problem there is an urgent need to create awareness about optimal use of the energy, environmental and economic benefits and making a nation more energy-independent, for this one of the obvious thought is combined heat and power (CHP) or cogeneration. In this paper performance of TVAC_PSO is tested ...

Motivated by an empirical analysis of ecological momentary assessment data (EMA) collected in a smoking cessation study, we propose a joint modeling technique for estimating the time-varying association between two intensively measured longitudinal responses: a continuous one and a binary one. A major challenge in joint modeling these responses is the lack of a multivariate distribution. We sug...

Dropout is a common occurrence in longitudinal studies. Building upon the pattern-mixture modeling approach within the Bayesian paradigm, we propose a general framework of varying-coefficient models for longitudinal data with informative dropout, where measurement times can be irregular and dropout can occur at any point in continuous time (not just at observation times) together with administr...