Bayesian's philosophy on Systematics

First, I’ll talk about the ideas and how we obtain them. Idea is defined as "an understanding, though, or picture in your mind" by Cambridge Dictionary (1), so I considered an idea as something that we obtained from previous knowledge but, how we get this knowledge? For that let's talk about Tolksdorf (2), he takes two different views and confronts them, the first is the knowledge as things that you can do, that suggest that theories are no-knowledge; the second defines knowledge as a cycle where you know that you really know. The author proposes knowledge as a thing that helps us to change from "beliefs" to "performance". So, in my opinion, the knowledge is based on experience, and theories are real-knowledge when are based on real data, that look more like the prospect of Plato (3), when he use epistemic analysis to differentiate between real stage with different opinion and which one is true; and look too like a kind of inductivism but explained by Hurley (4) where theories resulting from induction have a probability to be true or not.

The knowledge its taken as evidence for some theories but, how we test that theories or hypothesis? Well, to test hypothesis has to be based on personal postured, here I will talk about Bayesianism because it's my way to think. Maybe could be contradictory think to inductivism and Bayesian at the same time (5), but I referred to inductivism as the source of knowledge and Bayesian is the methodology to test a hypothesis based on prior knowledge (6).

So, how Bayesian works? Bayesian approach is "personal choice statistic" (7), firstly we have the empirical data and then we chose a prior, secondly evaluate how prior model your data and then calculate the posterior probability, that says how "good" or "bad" is your hypothesis for your data. A prior is a distribution's prospect for your data, here is the "personal choice", there are so many articles that develop this theme of choice prior (8) and the most are based on prior information and parameters assumption, but it's not my objective talk about this theme.

Given the above definitions of knowledge and Bayesian approach, therefore it’s time to discuss Systematics and Bayesian phylogenetics. Systematics is the discipline of biology that compares biological progress between animal, plants and all life's forms (9). Phylogenetic analysis studies the relationship between the organism and its principal aim is to find the common history and this could derive in a classification of species or clades -taxonomy- (10). Finally, Bayesian phylogenetics takes other statistics such as likelihood to estimate their prior tree and compare with data -evince of common history- (11), it seems to me a good way to estimate the true relationship between taxa. Furthermore, there's another conflict in phylogenetics relationship, how find the true phylogeny? That is impossible because the relationship could change even when we add or change data or evaluate different species (12). Finally, we just have probabilities, because we can't model all variables of evolution, and we won't ever know is that the real truth, this is the reason that I use the Bayesian approach to evaluate a phylogenetic hypothesis.

Reference

(1) Idea Meaning in the Cambridge English Dictionary. (n.d.). Retrieved September, 2018, from https://dictionary.cambridge.org/dictionary/english/idea

(2) Hetherington, S. (2011). Chapter One Knowledge, Ability, and Manifestation. In Conceptions of Knowledge (Vol. 4). Berlin, Germany: Technische Universität Berlin Institut für Philosophie.

(3) Plato. Book I, 344c. Plato Republic. Indianapolis: Hackett.

(4) Hurley, P. (2014).Chapter One: Basic Concepts. in A concise introduction to logic (Vol. 7). Nelson Education. pp 33-39

(5) Dorling, J., & Miller, D. (1981). Bayesian Personalism, Falsificationism, and the Problem of Induction. Proceedings of the Aristotelian Society, Supplementary Volumes, 55, 109-141.

(6) Hawthorne, J. (1993). Bayesian induction is eliminative induction. Philosophical Topics, 21(1), 99-138.

(7) Fienberg, S. E. (2006). When did Bayesian inference become" Bayesian"?. Bayesian analysis, 6-20.

(8) Yang, Z. (2008). Empirical evaluation of a prior for Bayesian phylogenetic inference. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 363(1512), 4031-4039.

(9) Kitching, I. J., Forey, P. L., Williams, D., & Humphries, C. (1998). Chapter One: Introduction. in Cladistics: the theory and practice of parsimony analysis (No. 11). Oxford University Press, USA.

(10) Futuyama, D. (2005) Chapter Two: Phylogeny. in Evolutionary Biology (3 ed.). New York: W.H. Freeman.

(11) Huelsenbeck, J. P., Rannala, B. and Masly, P. () An Introduction to Bayesian Inference of Phylogeny. Rochester: Department of Biology, University of Rochester.

(12) Nascimento, F. F., dos Reis, M., & Yang, Z. (2017). A biologist’s guide to Bayesian phylogenetic analysis. Nature ecology & evolution, 1(10), 1446.