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{ "item_title" : "Understanding the Tripartite Approach to Bayesian Divergence Time Estimation", "item_author" : [" Rachel C. M. Warnock", "April M. Wright "], "item_description" : "Placing evolutionary events in the context of geological time is a fundamental goal in paleobiology and macroevolution. In this Element we describe the tripartite model used for Bayesian estimation of time calibrated phylogenetic trees. The model can be readily separated into its component models: the substitution model, the clock model and the tree model. We provide an overview of the most widely used models for each component and highlight the advantages of implementing the tripartite model within a Bayesian framework.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/1/10/894/942/1108949428_b.jpg", "price_data" : { "retail_price" : "25.00", "online_price" : "25.00", "our_price" : "25.00", "club_price" : "25.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Understanding the Tripartite Approach to Bayesian Divergence Time Estimation|Rachel C. M. Warnock

Understanding the Tripartite Approach to Bayesian Divergence Time Estimation

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Overview

Placing evolutionary events in the context of geological time is a fundamental goal in paleobiology and macroevolution. In this Element we describe the tripartite model used for Bayesian estimation of time calibrated phylogenetic trees. The model can be readily separated into its component models: the substitution model, the clock model and the tree model. We provide an overview of the most widely used models for each component and highlight the advantages of implementing the tripartite model within a Bayesian framework.

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Details

  • ISBN-13: 9781108949422
  • ISBN-10: 1108949428
  • Publisher: Cambridge University Press
  • Publish Date: February 2021
  • Dimensions: 9 x 6 x 0.1 inches
  • Shipping Weight: 0.17 pounds
  • Page Count: 48

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