An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics

by   Liangliang Wang, et al.

The estimation of the probability of the data under a given evolutionary model has been an important computational challenge in Bayesian phylogenetic inference. In addition, inference for nonclock trees using sequential Monte Carlo (SMC) methods has remained underexploited. In this paper, we propose an annealed SMC algorithm with the adaptive determination of annealing parameters based on the relative conditional effective sample size for Bayesian phylogenetics. The proposed annealed SMC algorithm provides an unbiased estimator for the probability of the data. This unbiasedness property can be used for the purpose of testing the correctness of posterior simulation software. We evaluate the performance of phylogenetic annealed SMC by reviewing and comparing with other normalization constant estimation methods. Unlike the previous SMC methods in phylogenetics, the annealed SMC has the same state space for all the intermediate distributions, which allows standard Markov chain Monte Carlo (MCMC) tree moves to be utilized as the basis for SMC proposal distributions. Consequently, the annealed SMC should be relatively easy to incorporate into existing phylogenetic software packages based on MCMC algorithms. We illustrate our method using simulation studies and real data analysis.


page 1

page 2

page 3

page 4


Variational Combinatorial Sequential Monte Carlo Methods for Bayesian Phylogenetic Inference

Bayesian phylogenetic inference is often conducted via local or sequenti...

Fast Bayesian Deconvolution using Simple Reversible Jump Moves

We propose a Markov chain Monte Carlo-based deconvolution method designe...

Adaptive MCMC for Generalized Method of Moments with Many Moment Conditions

A generalized method of moments (GMM) estimator is unreliable when the n...

Generalized Bayesian Multidimensional Scaling and Model Comparison

Multidimensional scaling is widely used to reconstruct a map with the po...

How trustworthy is your tree? Bayesian phylogenetic effective sample size through the lens of Monte Carlo error

Bayesian inference is a popular and widely-used approach to infer phylog...

Toward Unlimited Self-Learning Monte Carlo with Annealing Process Using VAE's Implicit Isometricity

Self-learning Monte Carlo (SLMC) methods are recently proposed to accele...

An Introduction to Inductive Statistical Inference -- from Parameter Estimation to Decision-Making

These lecture notes aim at a post-Bachelor audience with a backgound at ...

Please sign up or login with your details

Forgot password? Click here to reset