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2.6: Models and Comparative Methods

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    For the rest of this book I will introduce several models that can be applied to evolutionary data. I will discuss how to simulate evolutionary processes under these models, how to compare data to these models, and how to use model selection to discriminate amongst them. In each section, I will describe standard statistical tests (when available) along with ML and Bayesian approaches.

    One theme in the book is that I emphasize fitting models to data and estimating parameters. I think that this approach is very useful for the future of the field of comparative statistics for three main reasons. First, it is flexible; one can easily compare a wide range of competing models to your data. Second, it is extendable; one can create new models and automatically fit them into a preexisting framework for data analysis. Finally, it is powerful; a model fitting approach allows us to construct comparative tests that relate directly to particular biological hypotheses.

    This page titled 2.6: Models and Comparative Methods is shared under a CC BY 4.0 license and was authored, remixed, and/or curated by Luke J. Harmon via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.

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