Usage
mcmc_sampling(dataset, alg, nsamp, nburnin = 0, nsubsamp = 1, ngrid = 100,
nugget = "1,1", prec_alpha = 0.01, prec_beta = 0.01, TrjL = NULL,
Nleap = NULL, szkappa = NULL, rand_leap = NULL, f_init = rep(1, ngrid
- 1), kappa = 1, covariates = NULL, betas = rep(0, 2 +
length(covariates)), samp_alg = "none", kappa_alg = "gibbs",
beta_vars = rep(100, length(betas)), printevery = 100)
Arguments
dataset
phylo object or list containing vectors of coalescent
times coal_times, sampling times samp_times, and number
sampled per sampling time n_sampled.
alg
string selecting which MCMC sampler to use. Options are "HMC",
"splitHMC", "MALA", "aMALA", and "ESS".
nsamp
integer number of MCMC steps to compute.
nburnin
integer number of MCMC steps to discard as burn-in.
nsubsamp
integer after burn-in, how often to record a step to the
output.
ngrid
integer number of grid point in the latent field.
nugget
string selecting which "nugget" adjustment to apply to the
precision matrix to make it full-rank. Options are '1,1' for an adjustment
to the first element, 'diag' for an adjustment to the entire main diagonal,
or 'none' which may result in a non-full-rank precision matrix.
prec_alpha, prec_beta
numeric shape and rate parameters for the prior
on precision.
TrjL
numeric tuning parameter.
Nleap
integer tuning parameter.
szkappa
numeric tuning parameter.
rand_leap
logical tuning parameter.
f_init
numeric vector starting log effective population size values.
kappa
numeric starting kappa.
covariates
list of functions representing covariate trajectories that
(may) influence sampling frequency.
betas
numeric vector of starting values for the beta hyperparameters.
samp_alg
string selecting sampling algorithm for sampling time
intensity coefficients. One of "none" (default), "fixed", "MH", and "ESS".
kappa_alg
selects sampling algorithm for kappa. One of "gibbs"
(default) or "whiten".
beta_vars
numeric vector prior variances of the beta hyperparameters.
printevery
integer how many MCMC steps between writing output to the
console.