Fast likelihood calculations for comparative analyses

1. Modern comparative approaches use model-based methods to describe evolutionary processes. Generalised least squares calculations lie at the heart of many methods; however, they can be computationally intensive. This is because it is necessary to form a variancecovariance matrix, then to calculate the inverse and determinant of this. 2. Based on an algorithm provided by Felsenstein (American Journal of Human Genetics, 1973, 25, 471), I show how to perform comparative calculations that avoid these computational steps. 3. I apply the method to several problems in comparative analysis, including calculating likelihoods, estimating Pagels ? for one or several traits and fitting linear models. 4. R code is provided, which implements the algorithm described. Examples are included to demonstrate the computational gains possible for several commonly used comparative methods.