mcmc_mix1_wrapper {crandep}

Wrapper of mcmc_mix1

Description

Wrapper of mcmc_mix1

Usage

mcmc_mix1_wrapper(
  df,
  seed,
  u_max = 2000L,
  log_diff_max = 11,
  a_psiu = 0.1,
  b_psiu = 0.9,
  m_alpha1 = 0,
  s_alpha1 = 10,
  a_theta1 = 1,
  b_theta1 = 1,
  m_alpha2 = 0,
  s_alpha2 = 10,
  positive = FALSE,
  iter = 20000L,
  thin = 1L,
  burn = 10000L,
  freq = 100L,
  invts = 1,
  mc3_or_marg = TRUE,
  x_max = 1e+05
)

Arguments

df

A data frame with at least two columns, x & count

seed

Integer for set.seed

u_max

Scalar (default 2000), positive integer for the maximum threshold to be passed to obtain_u_set_mix1

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_psiu, b_psiu, m_alpha1, s_alpha1, a_theta1, b_theta1, m_alpha2, s_alpha2

Scalars, real numbers representing the hyperparameters of the prior distributions for the respective parameters. See details for the specification of the priors.

positive

Boolean, is alpha1 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)

x_max

Scalar (default 100000), positive integer limit for computing the normalising constant

Value

A list returned by mcmc_mix1