mcmc_nltt: function, using a Monte Carlo Markov Chain

In richelbilderbeek/nLTT: Calculate the NLTT Statistic

function, using a Monte Carlo Markov Chain

Description

function, using a Monte Carlo Markov Chain

Usage

mcmc_nltt(
  phy,
  likelihood_function,
  parameters,
  logtransforms,
  iterations,
  burnin = round(iterations/3),
  thinning = 1,
  sigma = 1
)

Arguments

phy	phylo Vector of weights
likelihood_function	function Function that calculates the likelihood of our diversification model, given the tree. function should be of the format function(parameters, phy).
parameters	vector Initial parameters to start the chain.
logtransforms	scalar Whether to perform jumps on logtransformed parameters (TRUE) or not (FALSE)
iterations	scalar Length of the chain
burnin	scalar Length of the burnin, default is 30% of iterations
thinning	scalar Size of thinning, default = 1
sigma	scalar Standard deviation of the jumping distribution, which is N(0, sigma).

Value

mcmc An MCMC object, as used by the package "coda".

richelbilderbeek/nLTT documentation built on Aug. 23, 2023, 8 a.m.