results_optim_struct: Structure of the optimisation results data frames

In TheoPannetier/DDvTDtools: Compare diversity-dependent (DD) and time-dependent (TD) diversification models

Description

Returns a skeleton for the data frame in which the output of run_optim() is stored.

Usage

results_optim_struct()

Details

The dataset contains the following variables:

• sim factor, the name of the model used for simulation

• ntips numeric, the number of tips in the tree

• crown_age numeric, the crown age of the tree

• true_lambda0 numeric, the true value of λ_0

• true_mu0 numeric, the true value of μ_0

• true_K numeric, the true value of K

• mc numeric, the index of the tree (from 1 to 1000)

• optim factor, the model fit to the tree

• init_lambda0 numeric, the initial value of λ_0 used for optimisation

• init_mu0, numeric, the initial value of μ_0 used for optimisation

• init_k numeric, the initial value of K used for optimisation.

• loglik numeric, the log-likelihood of the fitted model

• AIC numeric, the AIC derived from the log-likelihood

• lambda0_ML numeric, the maximum likelihood estimate of λ_0

• mu0_ML numeric, the maximum likelihood estimate of μ_0

• K_ML, the maximum likelihood estimate of K.

• hasConverged logical, has the optimisation chain converged to a value?

• numCycles numeric, number of cycles of optimisation, run in a loop. See DDD::dd_ML()

• methode factor, the method used to solve the likelihood equation. See DDD::dd_ML()

• optimmethod factor, the method used for optimisation (either simplex or subplex). See DDD::dd_ML()

• jobID numeric, the ID of the job is the optimisation was run on a high-performance cluster.

• cond numeric, a code specifying how the likelihood is conditioned. See DDD::dd_ML()

Author(s)

Théo Pannetier

TheoPannetier/DDvTDtools documentation built on Oct. 22, 2020, 2:31 p.m.