macacaModels


Seven models of cranial landmark modularity. These models group the 61
  landmarks in <code><a rd-options="" href="/link/macacaCorrel?package=EMMLi&version=0.0.2" data-mini-rdoc="EMMLi::macacaCorrel">macacaCorrel</a></code> into modules. See  Goswami and 
  Finarelli (2016) for more details.


datasets

Fit models of modularity to morphological landmarks. Perform model
selection on results. Fit models with a single within-module correlation or
with separate within-module correlations fitted to each module.

Tim Lucas

EMMLi

A Maximum Likelihood Approach to the Analysis of Modularity

macacaModels function

A data frame with 61 rows (one for each landmark) and 8 coluumns. 
<ul>
<li>X.1Landmark names (character or factor)
 </li>
<li>Other columnsModel specification. Integers determine which module each landmark is 
   in. NAs indicate that a landmark is not in any module.
</li>
</ul>

Format

A. Goswami and J. Finarelli (2016) EMMLi: A maximum likelihood approach 
   to the analysis of modularity.
   Evolution <a href="http://onlinelibrary.wiley.com/doi/10.1111/evo.12956/abstract">http://onlinelibrary.wiley.com/doi/10.1111/evo.12956/abstract</a>.

Source


Seven models of cranial landmark modularity. These models group the 61
  landmarks in <code><a rd-options='' href='macacaCorrel'>macacaCorrel</a></code> into modules. See  Goswami and 
  Finarelli (2016) for more details.


A. Goswami and J. Finarelli (2016) EMMLi: A maximum likelihood approach 
   to the analysis of modularity.
   Evolution <a href = 'http://onlinelibrary.wiley.com/doi/10.1111/evo.12956/abstract'>http://onlinelibrary.wiley.com/doi/10.1111/evo.12956/abstract</a>.

macacaModels: Models of (Macaca fuscata) cranial modularity.

Description

Usage

Arguments

Format

Source

See Also