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z2kUG}#l{SN1IyNDl)X1)YQN5pf3E9g^sRpV4^YJutX FKLCm_R3iWY diff --git a/README.md b/README.md index 824d737..7381f43 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,41 @@ - + +[![R-CMD-check](https://github.com/nwfsc-timeseries/atsar/workflows/R-CMD-check/badge.svg)](https://github.com/nwfsc-timeseries/atsar/actions) + + + + The atsar R package implements Bayesian time series models using Stan, primarily for illustrative purposes and teaching (University of @@ -22,16 +59,12 @@ Simulate data: library(rstan) #> Loading required package: StanHeaders #> Loading required package: ggplot2 -#> rstan (Version 2.19.2, GitRev: 2e1f913d3ca3) +#> rstan (Version 2.21.2, GitRev: 2e1f913d3ca3) #> For execution on a local, multicore CPU with excess RAM we recommend calling #> options(mc.cores = parallel::detectCores()). #> To avoid recompilation of unchanged Stan programs, we recommend calling #> rstan_options(auto_write = TRUE) -#> For improved execution time, we recommend calling -#> Sys.setenv(LOCAL_CPPFLAGS = '-march=native') -#> although this causes Stan to throw an error on a few processors. library(atsar) -#> Loading required package: Rcpp set.seed(123) s = cumsum(rnorm(50)) ```