mcmc_mix3_wrapper: Wrapper of mcmc_mix3

Description

Wrapper of mcmc_mix3

Usage

mcmc_mix3_wrapper(
  df,
  seed,
  v_max = 100L,
  u_max = 2000L,
  log_diff_max = 11,
  a_psi1 = 1,
  a_psi2 = 1,
  a_psiu = 0.001,
  b_psiu = 0.9,
  m_alpha = 0,
  s_alpha = 10,
  a_theta = 1,
  b_theta = 1,
  m_shape = 0,
  s_shape = 10,
  a_sigma = 1,
  b_sigma = 0.01,
  a_pseudo = 10,
  b_pseudo = 1,
  pr_power2 = 0.5,
  powerlaw1 = FALSE,
  positive1 = FALSE,
  positive2 = TRUE,
  iter = 20000L,
  thin = 20L,
  burn = 100000L,
  freq = 1000L,
  invts = 1,
  mc3_or_marg = TRUE
)

Value

A list returned by mcmc_mix3

Arguments

df: A data frame with at least two columns, x & count
seed: Integer for set.seed
v_max: Scalar (default 100), positive integer for the maximum lower threshold to be passed to obtain_u_set_mix3
u_max: Scalar (default 2000), positive integer for the maximum upper threshold to be passed to obtain_u_set_mix3
log_diff_max: Positive real number, the value such that thresholds with profile posterior density not less than the maximum posterior density - log_diff_max will be kept
a_psi1, a_psi2, a_psiu, b_psiu, m_alpha, s_alpha, a_theta, b_theta, m_shape, s_shape, a_sigma, b_sigma: Scalars, real numbers representing the hyperparameters of the prior distributions for the respective parameters. See details for the specification of the priors.
a_pseudo: Positive real number, first parameter of the pseudoprior beta distribution for theta2 in model selection; ignored if pr_power2 = 1.0
b_pseudo: Positive real number, second parameter of the pseudoprior beta distribution for theta2 in model selection; ignored if pr_power2 = 1.0
pr_power2: Real number in [0, 1], prior probability of the discrete power law (between v and u)
powerlaw1: Boolean, is the discrete power law assumed for below v?
positive1: Boolean, is alpha1 positive (TRUE) or unbounded (FALSE)?
positive2: Boolean, is alpha2 positive (TRUE) or unbounded (FALSE)?
iter: Positive integer representing the length of the MCMC output
thin: Positive integer representing the thinning in the MCMC
burn: Non-negative integer representing the burn-in of the MCMC
freq: Positive integer representing the frequency of the sampled values being printed
invts: Vector of the inverse temperatures for Metropolis-coupled MCMC (if mc3_or_marg = TRUE) or power posterior (if mc3_or_marg = FALSE)
mc3_or_marg: Boolean, is Metropolis-coupled MCMC to be used? Ignored if invts = c(1.0)