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update installation instructions in the README
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README.Rmd

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@@ -63,10 +63,19 @@ help(brm)
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# How to install brms
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To install the latest release version from CRAN use
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```{r install_brms, eval=FALSE}
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install.packages("brms")
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```
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The current developmental version can be downloaded from github via
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```{r install_brms2, eval=FALSE}
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library(devtools)
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install_github("paul-buerkner/brms")
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```
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Because <b>brms</b> is based on Stan, a C++ compiler is required. The program Rtools (available on https://cran.r-project.org/bin/windows/Rtools/) comes with a C++ compiler for Windows. On Mac, you should use Xcode. We recommend to install rstan (available on CRAN) before installing <b>brms</b>. For further instructions see https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started.
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<!-- Before you will be able to actually fit bayesian models with brms, the package rstan has to be installed manually, as it is not on CRAN, yet. First, you need a C++ compiler. See https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started#prerequisites for instructions on how to get one. Second, install rstan by running the following R code (the number behind 'j' in the first line corresponds to the number of cores to use for the installation). This may take a few minutes and you should restart R after the installation.

README.md

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#> Data: epilepsy (Number of observations: 236)
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#> Samples: 2 chains, each with n.iter = 2000; n.warmup = 500; n.thin = 1;
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#> total post-warmup samples = 3000
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#> WAIC: Not computed
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#>
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#> Random Effects:
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#> ~patient (Number of levels: 59)
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methods(class = "brmsfit")
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#> [1] fixef formula hypothesis ngrps nobs par.names
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#> [7] plot posterior.samples predict print ranef summary
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#> [13] VarCorr
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#> [13] VarCorr WAIC
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#> see '?methods' for accessing help and source code
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```
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How to install brms
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===================
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To install the latest release version from CRAN use
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``` r
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install.packages("brms")
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```
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The current developmental version can be downloaded from github via
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``` r
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library(devtools)
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install_github("paul-buerkner/brms")
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```
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Because <b>brms</b> is based on Stan, a C++ compiler is required. The program Rtools (available on <https://cran.r-project.org/bin/windows/Rtools/>) comes with a C++ compiler for Windows. On Mac, you should use Xcode. We recommend to install rstan (available on CRAN) before installing <b>brms</b>. For further instructions see <https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started>.
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<!-- Before you will be able to actually fit bayesian models with brms, the package rstan has to be installed manually, as it is not on CRAN, yet. First, you need a C++ compiler. See https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started#prerequisites for instructions on how to get one. Second, install rstan by running the following R code (the number behind 'j' in the first line corresponds to the number of cores to use for the installation). This may take a few minutes and you should restart R after the installation.

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