fit_dd_model_with_fossil: Fit a diversity-dependent diversification model to...
In TheoPannetier/comrad: R implementation of a Competitive Radiation model

View source: R/fit_dd_model_with_fossil.R

fit_dd_model_with_fossil

R Documentation

Fit a diversity-dependent diversification model to phylogenies with fossil lineages

Description

Fits the parameters of a specified diversity-dependent model to a set of full phylogenies (with fossil lineages) produced by comrad simulations

Usage

fit_dd_model_with_fossil(
  waiting_times_tbl,
  init_params,
  dd_model = dd_model_lc(),
  num_cycles = Inf
)

Arguments

`waiting_times_tbl`	a table with waiting times, the output of `waiting_times()` for one or more phylogenies.
`init_params`	named vector, initial values of the parameters to optimise. The names and number of parameters must match those specified in `dd_model$params_check`.
`dd_model`	a list with five named elements that together specify the diversity-dependent model: `name` a two-letter code, the name of the model. First letter specifies the form of the speciation function, second letter the form of the extinction function: "l" for "linear", "x" for exponential, "c" for constant. `speciation_func`, a function specifying the diversity-dependent speciation rate. Must take arguments `params` and `N`. `extinction_func`, a function specifying the diversity-dependent extinction rate. Must take arguments `params` and `N`. `constraints` a list of conditions that parameter values must satisfy. Each element is a function that takes arguments `params` and `...`, and returns `TRUE` if the constraint is satisfied, `FALSE` if it isn't. `params_check` a function that controls the format of `params`. Returns an error if the elements of `params` are named differently from what is expected or if the length differs from the expectation. `comrad` contains several `dd_model` functions, see for example `dd_model_lc()`.
`num_cycles`	passed to `DDD::optimizer()`, number of cycles of optimisation. Next cycle starts from the last vertices of the previous cycle.

Value

a one-row table with initial values of the parameters, maximum likelihood estimates, the maximum likelihood and a convergence code (see subplex::subplex() for the meaning of this code)