Identifying an informative correlation structure is important in improving estimation efficiency for longitudinal data. We approximate the empirical estimator of the correlation matrix by groups of known basis matrices that represent different correlation structures, and transform the...

In this paper, we propose a quantile approach to the multi-index semiparametric model for an ordinal response variable. Permitting non-parametric transformation of the response, the proposed method achieves a root-<italic>n</italic> rate of convergence and has attractive robustness properties. Further, the...

The canonical correlation (CANCOR) method for dimension reduction in a regression setting is based on the classical estimates of the first and second moments of the data, and therefore sensitive to outliers. In this paper, we study a weighted canonical correlation (WCANCOR) method, which...

A new classifier, QIFC, is proposed based on the quadratic inference function for longitudinal data. Our approach builds a classifier by taking advantage of modeling information between the longitudinal responses and covariates for each class, and assigns a new subject to the class with the...