mcmc_pol_wrapper: Wrapper of mcmc_pol
In clement-lee/rackage: Network Analysis of Dependencies of CRAN Packages

mcmc_pol_wrapper

R Documentation

Wrapper of mcmc_pol

Description

Wrapper of mcmc_pol

Usage

mcmc_pol_wrapper(
  df,
  seed,
  alpha_init = 1.5,
  theta_init = 0.5,
  m_alpha = 0,
  s_alpha = 10,
  a_theta = 1,
  b_theta = 1,
  a_pseudo = 10,
  b_pseudo = 1,
  pr_power = 0.5,
  iter = 20000L,
  thin = 20L,
  burn = 100000L,
  freq = 1000L,
  invts = 0.001^((0:8)/8),
  mc3_or_marg = TRUE,
  xmax = 1e+05
)

Arguments

`df`	A data frame with at least two columns, x & count
`seed`	Integer for `set.seed`
`alpha_init`	Real number greater than 1, initial value of the parameter
`theta_init`	Real number in (0, 1], initial value of the parameter
`m_alpha`	Real number, mean of the prior normal distribution for alpha
`s_alpha`	Positive real number, standard deviation of the prior normal distribution for alpha
`a_theta`	Positive real number, first parameter of the prior beta distribution for theta; ignored if pr_power = 1.0
`b_theta`	Positive real number, second parameter of the prior beta distribution for theta; ignored if pr_power = 1.0
`a_pseudo`	Positive real number, first parameter of the pseudoprior beta distribution for theta in model selection; ignored if pr_power = 1.0
`b_pseudo`	Positive real number, second parameter of the pseudoprior beta distribution for theta in model selection; ignored if pr_power = 1.0
`pr_power`	Real number in [0, 1], prior probability of the discrete power law
`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)
`xmax`	Scalar (default 100000), positive integer limit for computing the normalising constant