Purpose: The purpose of this study is to discuss the phenomenon of dual-role participants in public-private partnership (PPP) projects. Contractors who are also investors hold a dual-role that can improve project financing and technical ability. However, speculation without effort from the...

Over the past two decades, many developing countries have grown to become more familiar with the notions and the use of public-private partnership/private financing initiative (PPP/PFI) schemes in building large-scale infrastructure assets. However, owing to higher levels of complexity and...

In Build-Operate-Transfer (BOT) infrastructure projects, host governments often provide subsidies, guarantees or alternative forms of support as incentives to attract private sector participation. A guaranteed level of minimum revenue, for example, can be specially designed to alleviate the...

We propose a class of general partially linear additive transformation models (GPLATM) with right-censored survival data in this work. The class of models are flexible enough to cover many commonly used parametric and nonparametric survival analysis models as its special cases. Based on the B...

The functional-coefficient regression models with different smoothing variables in different coefficient functions are discussed in this paper. The averaged estimates of coefficient functions are defined by averaging the sample on the initial value obtained by a local linear technique. Their...

In this paper, the functional-coefficient partially linear regression (FCPLR) model is proposed by combining nonparametric and functional-coefficient regression (FCR) model. It includes the FCR model and the nonparametric regression (NPR) model as its special cases. It is also a generalization...

Empirical-likelihood-based inference for the nonparametric parts in semiparametric varying-coefficient partially linear (SVCPL) models is investigated. An empirical log-likelihood approach to construct the confidence regions/intervals of the nonparametric parts is developed. An estimated...

In this paper, we consider variable selection for general transformation models with right censored data via nonconcave penalties. We will conduct the variable selection by maximizing the penalized log-marginal likelihood function. In the proposed variable selection procedures, we not only can...

Varying coefficient error-in-covariables models are considered with surrogate data and validation sampling. Without specifying any error structure equation, two estimators for the coefficient function vector are suggested by using the local linear kernel smoothing technique. The proposed...