R/richness_objective_bayes.R
objective_bayes_geometric.RdEstimate species richness with an objective Bayes method using a geometric model
objective_bayes_geometric(
data,
output = TRUE,
plot = TRUE,
answers = FALSE,
tau = 10,
burn.in = 100,
iterations = 2500,
Metropolis.stdev.N = 75,
Metropolis.start.theta = 1,
Metropolis.stdev.theta = 0.3
)A data.frame or tibble containing the frequency of frequencies data.
A logical value indicating whether the function should return the full posterior samples and diagnostic plots. Defaults to TRUE.
A logical value indicating whether to print a plot of the Markov Chain Monte Carlo diagnostic chains and posterior distribution. Defaults to TRUE.
A logical value indicating whether to return print-ready summary statistics and credible intervals. Defaults to FALSE.
An integer indicating the maximum frequency of the data to be analyzed. Defaults to 10.
An integer indicating the number of burn-in iterations for the Markov Chain Monte Carlo sampler. Defaults to 100.
An integer indicating the number of additional iterations for the Markov Chain Monte Carlo sampler after the burn-in iterations. Defaults to 2500.
A numeric value specifying the standard deviation for the Metropolis-Hastings proposal distribution of the parameter N. Defaults to 75.
Starting value in the Metropolis algorithm for the parameter theta. Defaults to 1.
A numeric value specifying the standard deviation for the Metropolis-Hastings proposal distribution of the parameter theta. Defaults to 0.3.
A list of results, including
the median of estimates of N
,
a confidence interval for N
,
the mean of estimates of N
,
the standard error of mean estimates
,
the DIC of the model
,
fitted values
, and
model diagonstics
.