mcmc_pol_wrapper | R Documentation |
Wrapper of mcmc_pol
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 = 1,
mc3_or_marg = TRUE,
x_max = 1e+05
)
df |
A data frame with at least two columns, x & count |
seed |
Integer for |
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) |
x_max |
Scalar (default 100000), positive integer limit for computing the normalising constant |
A list returned by mcmc_pol
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.