mbd_main: Run the full mbd routine
In Giappo/mbd: Multiple Birth Death Diversification

Simulate an mbd process and infer parameters maximizing the likelihood

mbd_main(
  sim_pars,
  cond = 1,
  n_0 = 2,
  age = 10,
  tips_interval = c(n_0 * (cond > 0), Inf),
  seed,
  start_pars = c(0.3, 0.1, 1.5, 0.15),
  optim_ids = rep(TRUE, length(start_pars)),
  ml_steps = 2,
  missnumspec = 0,
  loglik_functions = mbd::mbd_loglik,
  project_folder = NULL,
  verbose = FALSE,
  q_threshold = 1e-04,
  maxiter = 10000
)

`sim_pars`	vector of starting parameters: sim_pars[1] is lambda, the sympatric speciation rate; sim_pars[2] is mu, the extinction rate; sim_pars[3] is nu, the multiple allopatric speciation trigger rate; sim_pars[4] is q, the single-lineage speciation probability;
`cond`	sets the conditioning cond = 0: no conditioning; cond = 1: conditioning on stem or crown age and non-extinction of the phylogeny;
`n_0`	the number of lineages at time equals zero.
`age`	the age of the tree.
`tips_interval`	sets tips boundaries constrain on simulated dataset. It works only if cond == 1, otherwise it must be set to c(0, Inf).
`seed`	the seed
`start_pars`	starting parameter values for the ml process.
`optim_ids`	ids of the parameters you want to optimize.
`ml_steps`	number of increasing precision steps to adopt in the ml routine. Each step will increment the absolute and relative tolerances of the optimizer as well as the number of equations used by the likelihood function.
`missnumspec`	The number of species that are in the clade, but missing in the phylogeny.
`loglik_functions`	the loglik_functions you want to use
`project_folder`	the folder when you want to save data and results
`verbose`	choose if you want to print the output or not
`q_threshold`	adds a threshold for the evaluation of q. This is due because you never want `q` to actually be equal to zero or one.
`maxiter`	maximum number of subplex iterations