From 5491266517e71ebae3ba82199c379e21a08f0696 Mon Sep 17 00:00:00 2001 From: edknock Date: Wed, 23 Oct 2024 09:37:12 +0100 Subject: [PATCH] recompile docs --- man/monty_rng.Rd | 53 +++++++++++++++++++++++++ man/monty_sampler_nested_random_walk.Rd | 23 +---------- 2 files changed, 54 insertions(+), 22 deletions(-) diff --git a/man/monty_rng.Rd b/man/monty_rng.Rd index 4642f365..16a16425 100644 --- a/man/monty_rng.Rd +++ b/man/monty_rng.Rd @@ -143,6 +143,8 @@ rng$multinomial(5, 10, c(0.1, 0.3, 0.5, 0.1)) \item \href{#method-monty_rng-uniform}{\code{monty_rng$uniform()}} \item \href{#method-monty_rng-normal}{\code{monty_rng$normal()}} \item \href{#method-monty_rng-binomial}{\code{monty_rng$binomial()}} +\item \href{#method-monty_rng-beta_binomial_ab}{\code{monty_rng$beta_binomial_ab()}} +\item \href{#method-monty_rng-beta_binomial_prob}{\code{monty_rng$beta_binomial_prob()}} \item \href{#method-monty_rng-negative_binomial_prob}{\code{monty_rng$negative_binomial_prob()}} \item \href{#method-monty_rng-negative_binomial_mu}{\code{monty_rng$negative_binomial_mu()}} \item \href{#method-monty_rng-hypergeometric}{\code{monty_rng$hypergeometric()}} @@ -339,6 +341,57 @@ Generate \code{n} numbers from a binomial distribution \item{\code{prob}}{The probability of success on each trial (between 0 and 1, length 1 or n)} +\item{\code{n_threads}}{Number of threads to use; see Details} +} +\if{html}{\out{}} +} +} +\if{html}{\out{
}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-monty_rng-beta_binomial_ab}{}}} +\subsection{Method \code{beta_binomial_ab()}}{ +Generate \code{n} numbers from a beta-binomial distribution +\subsection{Usage}{ +\if{html}{\out{
}}\preformatted{monty_rng$beta_binomial_ab(n, size, a, b, n_threads = 1L)}\if{html}{\out{
}} +} + +\subsection{Arguments}{ +\if{html}{\out{
}} +\describe{ +\item{\code{n}}{Number of samples to draw (per stream)} + +\item{\code{size}}{The number of trials (zero or more, length 1 or n)} + +\item{\code{a}}{The first shape parameter (zero or more, length 1 or n)} + +\item{\code{b}}{The second shape parameter (zero or more, length 1 or n)} + +\item{\code{n_threads}}{Number of threads to use; see Details} +} +\if{html}{\out{
}} +} +} +\if{html}{\out{
}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-monty_rng-beta_binomial_prob}{}}} +\subsection{Method \code{beta_binomial_prob()}}{ +Generate \code{n} numbers from a beta-binomial distribution +\subsection{Usage}{ +\if{html}{\out{
}}\preformatted{monty_rng$beta_binomial_prob(n, size, prob, rho, n_threads = 1L)}\if{html}{\out{
}} +} + +\subsection{Arguments}{ +\if{html}{\out{
}} +\describe{ +\item{\code{n}}{Number of samples to draw (per stream)} + +\item{\code{size}}{The number of trials (zero or more, length 1 or n)} + +\item{\code{prob}}{The mean probability of sucess on each trial +(between 0 and 1, length 1 or n)} + +\item{\code{rho}}{The dispersion parameter (between 0 and 1, length 1 or n)} + \item{\code{n_threads}}{Number of threads to use; see Details} } \if{html}{\out{
}} diff --git a/man/monty_sampler_nested_random_walk.Rd b/man/monty_sampler_nested_random_walk.Rd index 58642a5f..e7ceecd7 100644 --- a/man/monty_sampler_nested_random_walk.Rd +++ b/man/monty_sampler_nested_random_walk.Rd @@ -4,12 +4,7 @@ \alias{monty_sampler_nested_random_walk} \title{Nested Random Walk Sampler} \usage{ -monty_sampler_nested_random_walk( - vcv, - boundaries = "reflect", - rerun_every = Inf, - rerun_random = FALSE -) +monty_sampler_nested_random_walk(vcv, boundaries = "reflect") } \arguments{ \item{vcv}{A list of variance covariance matrices. We expect this @@ -30,22 +25,6 @@ the domain. The initial point selected will lie within the domain, as this is enforced by \link{monty_sample}.} - -\item{rerun_every}{Optional integer giving the frequency at which -we should rerun the model on the current "accepted" parameters to -obtain a new density for stochastic models. The default for this -(\code{Inf}) will never trigger a rerun, but if you set to 100, then -every 100 steps we run the model on both the proposed \emph{and} previously -accepted parameters before doing the comparison. This may help "unstick" -chains, at the cost of some bias in the results.} - -\item{rerun_random}{Logical, controlling the behaviour of -rerunning (when \code{rerun_every} is finite). The default value of -\code{FALSE} will rerun the model at fixed intervals of iterations -(given by \code{rerun_every}). If \code{TRUE}, then we stochastically -rerun each step with probability of \code{1 / rerun_every}. This gives -the same expected number of MCMC steps between reruns but a different -pattern.} } \value{ A \code{monty_sampler} object, which can be used with