In this paper we extend the bivariate hazard ratio to multivariate competing risks data and show that it is equivalent to the cause-specific cross hazard ratio. Two approaches are proposed to estimate these two equivalent association measures. One extends the plug-in estimator, and the other...

Parametric modeling of univariate cumulative incidence functions and logistic models have been studied extensively. However, to the best of our knowledge, there is no study using logistic models to characterize cumulative incidence functions. In this paper, we propose a novel parametric model...

This article aimed to research the spatial distribution and operation conditions of the recent low-carbon industrial clusters in China and make suggestions for future development. Location quotient method was used to identify industrial cluster. With this method, the article calculated the...

It is often important to study the association between two continuous variables. In this work, we propose a novel regression framework for assessing conditional associations on quantiles. We develop general methodology which permits covariate effects on both the marginal quantile models for the...

We propose an alternative representation of the cause-specific cross hazard ratio for bivariate competing risks data. The representation leads to a simple plug-in estimator, unlike an existing ad hoc procedure. The large sample properties of the resulting inferences are established. Simulations...

The "plug-in" quadratic discriminant function is common in discriminant analysis. However, this function performs poorly for high dimensional populations. We propose an alternate procedure which performs much better in the case of high dimensional data.