This paper presents an interactive study on the relationship between the foreign trade structure, opening degree and economic growth of the provinces in western China (except Tibet). It shows that the export of primary products and labor-intensive products has a positive impact on the external...

This paper considers estimation and inference for varying-coefficient models with nonstationary regressors. We propose a nonparametric estimation method using penalized splines, which achieves the same optimal convergence rate as kernel-based methods, but enjoys computation advantages. Utilizing...

The Financial Risk Meter (FRM) is an established mechanism that, based on conditional Value at Risk (VaR) ideas, yields insight into the dynamics of network risk. Originally, the FRM has been composed via Lasso based quantile regression, but we here extend it by incorporating the idea of...

K-means clustering is one of the most widely-used partitioning algorithm in cluster analysis due to its simplicity and computational efficiency, but it may not provide ideal clustering results when applying to data with non-spherically shaped clusters. By considering the asymmetrically weighted...

This paper considers smooth principle component analysis for high dimensional data with very large dimensional observations p and moderate number of individuals N. Our setting is similar to traditional PCA, but we assume the factors are smooth and design a new approach to estimate them. By...

In this paper, we propose a new class of regime shift models with exible switching mechanism that relies on a nonparametric probability function of the observed thresh- old variables. The proposed models generally embrace traditional threshold models with contaminated threshold variables or...

In this paper, we propose a new class of regime shift models with flexible switching mechanism that relies on a nonparametric probability function of the observed threshold variables. The proposed models generally embrace traditional threshold models with contaminated threshold variables or...

The Financial Risk Meter (FRM) is an established mechanism that, based on conditional Value at Risk (VaR) ideas, yields insight into the dynamics of network risk. Originally, the FRM has been composed via Lasso based quantile regression, but we here extend it by incorporating the idea of...

K-means clustering is one of the most widely-used partitioning algorithm in cluster analysis due to its simplicity and computational efficiency, but it may not provide ideal clustering results when applying to data with non-spherically shaped clusters. By considering the asymmetrically weighted...