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TDKcAs_5^v#^!uW}INtg<4VB|G diff --git a/docs/reference/cmdstanr-package.html b/docs/reference/cmdstanr-package.html index 1208c80d2..5cd82a34f 100644 --- a/docs/reference/cmdstanr-package.html +++ b/docs/reference/cmdstanr-package.html @@ -133,13 +133,10 @@

Different ways of interfac

Advantages of RStan

-
  • Advanced features. We are working on making these available outside of -RStan but currently they are only available to R users via RStan:

  • -
  • Allows other developers to distribute R packages with pre-compiled +

    • Allows other developers to distribute R packages with pre-compiled Stan programs (like rstanarm) on CRAN.

    • +
    • Avoids use of R6 classes, which may result in more familiar syntax for +many R users.

@@ -151,7 +148,6 @@

Advantages of CmdStanRStanHeaders. With CmdStanR the latest improvements in Stan will be available from R immediately after updating CmdStan using cmdstanr::install_cmdstan().

-
  • Fewer installation issues (e.g., no need to mess with Makevars files).

  • Running Stan via external processes results in fewer unexpected crashes, especially in RStudio.

  • Less memory overhead.

  • @@ -199,6 +195,7 @@

    Examples

    # here using the example model that comes with CmdStan file <- file.path(cmdstan_path(), "examples/bernoulli/bernoulli.stan") mod <- cmdstan_model(file) +#> Model executable is up to date! mod$print() #> data { #> int<lower=0> N; @@ -334,7 +331,7 @@

    Examples

    # Call CmdStan's diagnose and stansummary utilities fit_mcmc$cmdstan_diagnose() -#> Processing csv files: /var/folders/s0/zfzm55px2nd2v__zlw5xfj2h0000gn/T/RtmpFBtN6X/bernoulli-202307251435-1-2078cc.csv, /var/folders/s0/zfzm55px2nd2v__zlw5xfj2h0000gn/T/RtmpFBtN6X/bernoulli-202307251435-2-2078cc.csv +#> Processing csv files: /var/folders/s0/zfzm55px2nd2v__zlw5xfj2h0000gn/T/Rtmp9Z3PNu/bernoulli-202307271729-1-67e85d.csv, /var/folders/s0/zfzm55px2nd2v__zlw5xfj2h0000gn/T/Rtmp9Z3PNu/bernoulli-202307271729-2-67e85d.csv #> #> Checking sampler transitions treedepth. #> Treedepth satisfactory for all transitions. @@ -406,8 +403,8 @@

    Examples

    #> This procedure has not been thoroughly tested and may be unstable #> or buggy. The interface is subject to change. #> ------------------------------------------------------------ -#> Gradient evaluation took 6e-06 seconds -#> 1000 transitions using 10 leapfrog steps per transition would take 0.06 seconds. +#> Gradient evaluation took 5e-06 seconds +#> 1000 transitions using 10 leapfrog steps per transition would take 0.05 seconds. #> Adjust your expectations accordingly! #> Begin eta adaptation. #> Iteration: 1 / 250 [ 0%] (Adaptation) @@ -505,7 +502,7 @@

    Examples

    #> #> Both chains finished successfully. #> Mean chain execution time: 0.0 seconds. -#> Total execution time: 0.4 seconds. +#> Total execution time: 0.3 seconds. #> fit_optim_w_init_list <- mod$optimize( data = stan_data,