Doc updates

NAMESPACE

@@ -28,6 +28,7 @@ export(monty_model_gradient)
 export(monty_model_properties)
 export(monty_observer)
 export(monty_packer)
+export(monty_packer_grouped)
 export(monty_rng)
 export(monty_rng_distributed_pointer)
 export(monty_rng_distributed_state)

R/runner.R

@@ -53,17 +53,17 @@ monty_runner_serial <- function(progress = NULL) {
 
 ##' Run MCMC chains in parallel (at the same time).  This runner uses
 ##' the `parallel` package to distribute your chains over a number of
-##' worker processes on the same machine.  Compared with the "worker"
-##' support in `mcstate` version 1 this is very simple and we'll improve
-##' it over time.  In particular we do not report back any information
-##' about progress while a chain is running on a worker or even across
-##' chains.  There's also no support to warn you if your number of
-##' chains do not neatly divide through by the number of workers.
-##' Mostly this exists as a proof of concept for us to think about the
-##' different interfaces.  Unless your chains are quite slow, the
-##' parallel runner will be slower than the serial runner
-##' ([monty_runner_serial]) due to the overhead cost of starting the
-##' cluster.
+##' worker processes on the same machine.  Compared with
+##' [monty_runner_callr] (Whch is similar to the "worker" support in
+##' `mcstate` version 1), this is very simple.  In particular we do
+##' not report back any information about progress while a chain is
+##' running on a worker or even across chains.  There's also no
+##' support to warn you if your number of chains do not neatly divide
+##' through by the number of workers.  Mostly this exists as a proof
+##' of concept for us to think about the different interfaces.  Unless
+##' your chains are quite slow, the parallel runner will be slower
+##' than the serial runner ([monty_runner_serial]) due to the overhead
+##' cost of starting the cluster.
 ##'
 ##' @title Run MCMC chain in parallel
 ##'

README.md

@@ -31,7 +31,6 @@ The [`odin2`](https://mrc-ide.github.io/odin2/) package can generate dynamical m
 
 The basic functionality of this package is in place, but we plan to do work on:
 
-* expanding runners to include parallel chains (a basic parallel runner exists, but we will port over the `callr`-based runner from `mcstate`)
 * improving debugging tools if models fail mid-chain
 * implementing parallel tempering, allowing you to compose with any other supported sampler
 * improving support for nested models