Alternative algorithms for the estimation of dynamic factor, mimic and varying coefficient regression models

Varying-Coefficient Functional Linear Regression Models

We propose in this work a generalization of the functional linear model in which an additional real variable influences smoothly the functional coefficient. This leads us to build a varying-coefficient regressionmodel for functional data. We propose two estimators based respectively on conditional functional principal regression and on local penalized regression splines and prove their pointwis...

Efficient Estimation in Heteroscedastic Varying Coefficient Models

This paper considers statistical inference for the heteroscedastic varying coefficient model. We propose an efficient estimator for coefficient functions that is more efficient than the conventional local-linear estimator. We establish asymptotic normality for the proposed estimator and conduct some simulation to illustrate the performance of the proposed method.

Boosted Varying-Coefficient Regression Models for Product Demand Prediction

Estimating the aggregated market demand for a product in a dynamic market is critical to manufacturers and retailers. Motivated by the need for a statistical demand prediction model for laptop pricing at Hewlett-Packard, we have developed a novel boosting-based varying-coefficient regression model. The developed model uses regression trees as the base learner, and is generally applicable to var...

Inference for Covariate Adjusted Regression via Varying Coefficient Models

We consider covariate adjusted regression (CAR), a regression method for situations where predictors and response are observed after being distorted by a multiplicative factor. The distorting factors are unknown functions of an observable covariate, where one specific distorting function is associated with each predictor or response. The dependence of both response and predictors on the same co...

Efficient estimation and inferences for varying-coefficient models