Generalized iterative scaling (GIS) has become a popular method for getting the maximum likelihood estimates for log-linear models. It is basically a sequence of successive I-projections onto sets of probability vectors with some given linear combinations of probability vectors. However, when a...

Regression analysis of the odds ratios for sparse data has received a lot of attention. However, existing works are restricted to the parametric case, and a parametric model may be a misspecification, which may lead to biased and inefficient estimators. Little attention is received for...

This paper identifies and estimates the relative average treatment effect in the presence of misclassification. We propose consistent estimators based on nonparametric methods. The simulation results reported illustrate the performance of the proposed estimators.

type="main" xml:id="sjos12057-abs-0001" <title type="main">ABSTRACT</title>Motivated by an entropy inequality, we propose for the first time a penalized profile likelihood method for simultaneously selecting significant variables and estimating unknown coefficients in multiple linear regression models in this article. The...

Purpose Visual tracking technology enables industrial robots interacting with human beings intelligently. However, due to the complexity of the tracking problem, the accuracy of visual target tracking still has great space for improvement. This paper aims to propose an accurate visual target...

Aimed at providing the anticipatory ability for the proactive traffic control systems, a new adaptive online short-term univariate traffic condition forecasting method is presented in this dissertation by assimilating knowledge from previous research. Using 15-minute traffic flow series as a...