stop_chain {BeviMed} | R Documentation |
Apply the MCMC algorithm in blocks until conditions are met
Description
Sample blocks of a given size until either the estimated log marginal likelihood falls within a given confidence interval, there is sufficient confidence that the evidence model gamma = 1 is at most a certain quantity, or a certain number of blocks have been sampled.
Usage
stop_chain(
y,
blocks_remaining,
start_zs,
start_logit_omegas,
start_log_phis,
temperatures,
tolerance = 1,
confidence = 0.95,
simulations = 1000,
log_evidence_threshold = -Inf,
y_log_lik_t_equals_1_traces = matrix(ncol = length(temperatures), nrow = 0),
full_block_traces = list(),
verbose = FALSE,
...
)
Arguments
y |
Logical vector of case ( |
blocks_remaining |
Maximum number of blocks left before termination. |
start_zs |
Initial (logical) z-matrix. |
start_logit_omegas |
Initial values of logit_omega (numeric vector - one value per chain). |
start_log_phis |
Initial values of log_phi (numeric vector - one value per chain). |
temperatures |
Numeric vector of temperatures of power posteriors. One chain will be created for each element of the vector at the corresponding temperature. |
tolerance |
Maximum width for confidence_interval of log marginal likelihood to allow before stopping the chain. |
confidence |
Numeric value of statistical confidence with which returning interval should contain the true value. |
simulations |
Integer value of number of simulations to use in estimation of the confidence interval. |
log_evidence_threshold |
Numeric value used to determine whether to stop the sampling procedure after successive blocks. If we are confident (to the level of |
y_log_lik_t_equals_1_traces |
Numeric matrix of log probabilities of |
full_block_traces |
List of outputs of calls to MCMC routine. |
verbose |
To print execution progress or not. |
... |
Other arguments passed to |
Value
An object of class BeviMed
.