Complementing this, studies on QR-based estimators in partially linear models with correlated errors have extended the utility of cross validation techniques in selecting shrinkage parameters ...

Prediction is often the primary goal of data analysis. In this work, we propose a novel model averaging approach to the prediction of a functional response variable. We develop a crossvalidation model ...

Ignoring measurement errors in conventional regression analyses can lead to biased estimation and inference results. Reducing such bias is challenging when the error-prone covariate is a functional ...

estimation and prediction of linear regression models with autoregressive errors any order autoregressive or subset autoregressive process optional stepwise selection of autoregressive parameters ...

Ordinary regression analysis is based on several statistical assumptions. One key assumption is that the errors are independent of each other. However, with time series data, the ordinary regression ...