ArticleSystematic biology2012
Assessing parameter identifiability in phylogenetic models using data cloning.
Article in Systematic biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
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- Evidence of an Absence of Inbreeding Depression in a Wild Population of Weddell Seals (Entropy (Basel, Switzerland) · 2023Article
- PrioriTree: a utility for improving phylodynamic analyses in BEAST.Bioinformatics (Oxford, England) · 2023Article
- Entropy, Statistical Evidence, and Scientific Inference: Evidence Functions in Theory and Applications.Entropy (Basel, Switzerland) · 2022Article
- Pulled Diversification Rates, Lineages-Through-Time Plots, and Modern Macroevolutionary Modeling.Systematic biology · 2022Article
- Coalescence modeling of intrainfectionProceedings of the National Academy of Sciences of the United States of America · 2020Article
- Model Projections in Model Space: A Geometric Interpretation of the AIC Allows Estimating the Distance Between Truth and Approximating Models.Frontiers in ecology and evolution · 2019Article
- ModelingInternational journal of environmental research and public health · 2019Review
- Strong Evidence for an Intraspecific Metabolic Scaling Coefficient Near 0.89 in Fish.Frontiers in physiology · 2019Article
- chromploid: An R package for chromosome number evolution across the plant tree of life.Applications in plant sciences · 2018Article
- An efficient extension of N-mixture models for multi-species abundance estimation.Methods in ecology and evolution · 2018Article
- Integrating Crop Growth Models with Whole Genome Prediction through Approximate Bayesian Computation.PloS one · 2015Article
- Density-dependent state-space model for population-abundance data with unequal time intervals.Ecology · 2014Article
- From algae to angiosperms-inferring the phylogeny of green plants (Viridiplantae) from 360 plastid genomes.BMC evolutionary biology · 2014Article
- Predicting the process of extinction in experimental microcosms and accounting for interspecific interactions in single-species time series.Ecology letters · 2014Article
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4 authors.
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Abstract
The success of model-based methods in phylogenetics has motivated much research aimed at generating new, biologically informative models. This new computer-intensive approach to phylogenetics demands validation studies and sound measures of performance. To date there has been little practical guidance available as to when and why the parameters in a particular model can be identified reliably. Here, we illustrate how Data Cloning (DC), a recently developed methodology to compute the maximum likelihood estimates along with their asymptotic variance, can be used to diagnose structural parameter nonidentifiability (NI) and distinguish it from other parameter estimability problems, including when parameters are structurally identifiable, but are not estimable in a given data set (INE), and when parameters are identifiable, and estimable, but only weakly so (WE). The application of the DC theorem uses well-known and widely used Bayesian computational techniques. With the DC approach, practitioners can use Bayesian phylogenetics software to diagnose nonidentifiability. Theoreticians and practitioners alike now have a powerful, yet simple tool to detect nonidentifiability while investigating complex modeling scenarios, where getting closed-form expressions in a probabilistic study is complicated. Furthermore, here we also show how DC can be used as a tool to examine and eliminate the influence of the priors, in particular if the process of prior elicitation is not straightforward. Finally, when applied to phylogenetic inference, DC can be used to study at least two important statistical questions: assessing identifiability of discrete parameters, like the tree topology, and developing efficient sampling methods for computationally expensive posterior densities.
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