################################################################################
#
# RevBayes: Discrete morphology tutorials -- among-character rate variation (ACRV)
#           using a discretized Gamma distribution
#
################################################################################

# Create the Q matrix. These data are binary, so we initialize the Jukes-Cantor
# matrix with two states.
Q_morpho <- fnJC(2)

# Set up Gamma-distributed rate variation, using a uniform prior between 0 and
# 10^8, as recommended by Fabreti and Hoehna (2023)
alpha_morpho ~ dnUniform( 0.0, 1E8 )
alpha_morpho.setValue( 1.0 )
rates_morpho := fnDiscretizeGamma( alpha_morpho, alpha_morpho, 4 )

# Moves on the parameter of the Gamma distribution.
moves.append( mvScale(alpha_morpho, lambda=1, weight=2.0) )

# Combine all of our elements into a CTMC. Because we have not observed any
# invariant sites, we specify the coding as 'variable'.
phyMorpho ~ dnPhyloCTMC(tree=phylogeny, siteRates=rates_morpho, Q=Q_morpho, type="Standard", coding="variable")
phyMorpho.clamp(morpho)