Summary:

Regarding the parameters of the dual averaging optimization for the stepsize in the warmup, all parameters can be set by the user except mu. For certain models, the initial choice of mu can result in a drastic drop of the stepsize for subsequent iterations. This might lead to extra computation time. As mu is adjusted for each window of the mass matrix adjustment, this can in e

Summary:

Documentation of optimizing does not appear accurate, specifically the init parameter

Description:

The description of the init parameter of optimizing is identical to that of sampling, with reference to chains, which optimizing does not use (as far as I understand).

Behavior does not seem to correlate with choices of init either. For example, initializing

This should reduce the number of duplicated documentation snippets and replace @inheritParams tags.

Summary:

Right now there is a wiki page:

https://github.com/stan-dev/rstan/wiki/RStan-Mojave-Mac-OS-X-Prerequisite-Installation-Instructions

about a particular aspect of Mac OS X installation. Can we roll that into the basic install instructions?

https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started

Otherwise, I fear people won't find it. Right now, there's a bunch of

It is not clear from the documentation what the intended usage is for outputs from stan_lm or stan_lm where you do not have hierarchies to pass to gather_draws() or spread_draws().

For example, fitting a very simple model with stan_lm():

library(tidyverse)
library(rstan)
library(rstanarm)
library(tidybayes)

test_stanlm <- stan_lm(mpg ~ cyl + disp + hp + drat + wt + vs +

Description

In the constrain_XXX functions applied to map unconstrained parameters to parameters in Stan, the value being constrained is required to be the same type as the log density target being incremented. These functions should allow the two types to vary independently. The target will always be at least double, whereas the variable being constrained might be int when used in t

@bgoodri I just noticed that none of the CRAN versions of the vignettes have any output from the code chunk no output anymore (e.g. if you look at https://cran.r-project.org/web/packages/rstanarm/vignettes/count.html
or any of the other vignettes). That is, it looks like none of the code is getting evaluated. I know that we're using that mechanism with params$EVAL to avoid evaluating the vignet

Just noticed that this isn’t discussed anywhere, but the PPC functions have always also been very useful for prior predictive checking, not just posterior checking.

It would be helpful to have a NatsStreamingCluster example with all possible options just to see everything that is available.

For example in one of the examples it shows setting spec.config.storeDir. what other options are available here other than storeDir?

決まったら Wiki に移す。

基本方針

• オリジナルソースから持ってくる。
  stan リポジトリで翻訳対象の文で検索すればおそらく見つかりやすい。
• 編集の都合で改行を削除して 1 行にする。

マクロ (案)