Functional principal component regression (FPCR) is a promising new method for regressing scalar outcomes on functional predictors. In this article, we present a theoretical justification for the use ...

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 40, No. 4, Special Issue in Honour of Mary Thompson (December/décembre 2012), pp. 745-769 (25 pages) In this paper, we ...

Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...

Generally speaking, there are two types of outcomes (i.e. response) in statistical analysis: continuous and categorical responses. Linear Models (LM) are one of the most commonly used statistical ...