Since the mid 1980's many statisticians have studied methods for combining parametric andnonparametric esimates to improve the quality of fits in a regression problem. Notably in 1987,Einsporn and Birch proposed the Model Robust Regression estimate (MRR1) in which estimatesof the parametric...

Most traditional parametric and nonparametric regression methods operate under the assumption that the true function is continuous over the design space. For methods such as ordinary least squares polynomial regression and local polynomial regression the functional estimates are constrained to...

The generalized linear model (GLM) is a popular model in many research areas. In theGLM, each outcome of the dependent variable is assumed to be generated from a particulardistribution function in the exponential family. The mean of the distribution depends onthe independent variables. The link...

This research is motivated by an issue frequently encountered in water quality monitoring and ecological assessment. One concern for researchers and watershed resource managers is how the biological community in a watershed is affected by human activities. The conventional single model approach...

In typical normal theory regression, the assumption ofhomogeneity of variances is often not appropriate.Instead of treating the variances as a nuisance andtransforming away the heterogeneity, the structure ofthe variances may be of interest and it is desirable tomodel the variances. Aitkin...

Time Series of water quality variables typically possess many of several characteristics which complicate analysis. Of interest to researchers is often the trend over time of the water quality variable. However, sometimes water quality variable levels appear to increase or decrease monotonically...