| hurdle_control {hurdlr} | R Documentation |
Control Parameters for Hurdle Model Count Data Regression
Description
Various parameters for fitting control of hurdle
model regression using hurdle.
Usage
hurdle_control(a = 1, b = 1, size = 1, beta.prior.mean = 0,
beta.prior.sd = 1000, beta.tune = 1, pars.tune = 0.2, lam.start = 1,
mu.start = 1, sigma.start = 1, xi.start = 1)
Arguments
a |
shape parameter for gamma prior distributions. |
b |
rate parameter for gamma prior distributions. |
size |
size parameter for negative binomial likelihood distributions. |
beta.prior.mean |
mu parameter for normal prior distributions. |
beta.prior.sd |
standard deviation for normal prior distributions. |
beta.tune |
Markov-chain tuning for regression coefficient estimation. |
pars.tune |
Markov chain tuning for parameter estimation of 'extreme' observations distribution. |
lam.start |
initial value for the poisson likelihood lambda parameter. |
mu.start |
initial value for the negative binomial or log normal likelihood mu parameter. |
sigma.start |
initial value for the generalized pareto likelihood sigma parameter. |
xi.start |
initial value for the generalized pareto likelihood xi parameter. |
Value
A list of all input values.
Author(s)
Taylor Trippe <ttrippe@luc.edu>
Earvin Balderama <ebalderama@luc.edu>