From c30c192b886f9dc933251f760545b342faac6844 Mon Sep 17 00:00:00 2001 From: Ben Goodrich Date: Wed, 2 Oct 2019 09:49:09 -0400 Subject: [PATCH] just take relative URLs out of vignettes --- DESCRIPTION | 4 ++-- vignettes/glmer.Rmd | 6 +++--- vignettes/lm.Rmd | 3 ++- 3 files changed, 7 insertions(+), 6 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index ef6ce9fca..54e22d2ab 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,8 +1,8 @@ Package: rstanarm Type: Package Title: Bayesian Applied Regression Modeling via Stan -Version: 2.19.1 -Date: 2019-09-16 +Version: 2.19.2 +Date: 2019-10-01 Encoding: UTF-8 Authors@R: c(person("Jonah", "Gabry", email = "jsg2201@columbia.edu", role = "aut"), person("Imad", "Ali", role = "ctb"), diff --git a/vignettes/glmer.Rmd b/vignettes/glmer.Rmd index 3c0f21550..6b7fa37e9 100644 --- a/vignettes/glmer.Rmd +++ b/vignettes/glmer.Rmd @@ -22,9 +22,9 @@ params: This vignette explains how to use the `stan_lmer`, `stan_glmer`, `stan_nlmer`, and `stan_gamm4` functions in the __rstanarm__ package to estimate linear and generalized (non-)linear models with parameters that may vary across groups. -Before continuing, we recommend reading the [vignettes](glm.html) for the -`stan_glm` function. The _Hierarchical Partial Pooling_ [vignette](pooling.html) -also has examples of both `stan_glm` and `stan_glmer`. +Before continuing, we recommend reading the vignettes (navigate up one level) for +the various ways to use the `stan_glm` function. The _Hierarchical Partial Pooling_ +vignette also has examples of both `stan_glm` and `stan_glmer`. # GLMs with group-specific terms diff --git a/vignettes/lm.Rmd b/vignettes/lm.Rmd index a605c4759..ed7c4bbfb 100644 --- a/vignettes/lm.Rmd +++ b/vignettes/lm.Rmd @@ -330,7 +330,8 @@ distributions thoughtfully and take a short-cut by specifying one prior distribution that is taken to apply to all the regression coefficients as if they were independent of each other (and the intercept and error variance). This short-cut is available in the `stan_glm` function and is described in more -detail in other __rstanarm__ [vignette](glm.html) for Generalized Linear Models (GLMs). +detail in other __rstanarm__ vignettes for Generalized Linear Models (GLMs), +which can be found by navigating up one level. We are optimistic that this prior on the $R^2$ will greatly help in accomplishing our goal for __rstanarm__ of making Bayesian estimation of regression models