update_pars: MCMC Third-Component Parameter Update Function for Hurdle...
In hurdlr: Zero-Inflated and Hurdle Modelling Using Bayesian Inference

MCMC algorithm for updating the third-component likelihood parameters in hurdle model regression using hurdle.

1 2	update_pars(y, hurd, dist, like.part, a, b, size, lam, mu, xi, sigma, lam.acc, mu.acc, xi.acc, sigma.acc, lam.tune, mu.tune, xi.tune, sigma.tune, g.x = F)

`y`	numeric response vector of observations within the bounds of the third component of the likelihood function, y[y ≥ hurd].
`hurd`	numeric threshold for 'extreme' observations of two-hurdle models.
`dist`	character specification of response distribution for the third component of the likelihood function.
`like.part`	numeric vector of the current third-component likelihood values.
`a`	shape parameter for gamma prior distributions.
`b`	rate parameter for gamma prior distributions.
`size`	size parameter for negative binomial likelihood distributions.
`lam`	current value for the poisson likelihood lambda parameter.
`mu`	current value for the negative binomial or log normal likelihood mu parameter.
`xi`	current value for the generalized pareto likelihood xi parameter.
`sigma`	current value for the generalized pareto likelihood sigma parameter.
`lam.acc, mu.acc, xi.acc, sigma.acc`	current MCMC values for third-component parameter acceptance rates.
`lam.tune, mu.tune, xi.tune, sigma.tune`	current MCMC tuning values for each third-component parameter.
`g.x`	logical operator. `TRUE` if operating within the third component of the likelihood function (the likelihood of 'extreme' observations).