, Daniel Adler [aut],
Thomas Kneib [aut], Stefan Lang [aut], Achim Zeileis [aut]
| Title: | Distribution of the 'BayesX' C++ Sources |
|---|---|
| Description: | 'BayesX' performs Bayesian inference in structured additive regression (STAR) models. The R package BayesXsrc provides the 'BayesX' command line tool for easy installation. A convenient R interface is provided in package R2BayesX. |
| Authors: | Nikolaus Umlauf [aut, cre]
, Daniel Adler [aut],
Thomas Kneib [aut], Stefan Lang [aut], Achim Zeileis [aut]
|
| Maintainer: | Nikolaus Umlauf <[email protected]> |
| License: | GPL-2 | GPL-3 |
| Version: | 3.0-5 |
| Built: | 2025-02-09 03:59:01 UTC |
| Source: | https://github.com/cran/BayesXsrc |
Run BayesX program files from R.
run.bayesx(prg = NULL, verbose = TRUE, ...)run.bayesx(prg = NULL, verbose = TRUE, ...)
prg |
a file path to a BayesX program file. If set to |
verbose |
should output be printed to the R console during runtime of BayesX. |
... |
further arguments to be passed to |
Function uses system to run BayesX within an R session.
If a prg file is provided, the function returns a list containg information if
BayesX was succesfully launched and how long the process was running.
Daniel Adler, Thomas Kneib, Stefan Lang, Nikolaus Umlauf, Achim Zeileis.
## Not run: ## create a temporary directory for this example dir <- tempdir() prg <- file.path(dir, "demo.prg") ## generate some data set.seed(111) n <- 200 ## regressor dat <- data.frame(x = runif(n, -3, 3)) ## response dat$y <- with(dat, 1.5 + sin(x) + rnorm(n, sd = 0.6)) ## write data to dir write.table(dat, file.path(dir, "data.raw"), quote = FALSE, row.names = FALSE) ## create the .prg file writeLines(" bayesreg b dataset d d.infile using data.raw b.outfile = mcmc b.regress y = x(psplinerw2,nrknots=20,degree=3), family=gaussian predict using d b.getsample", prg) ## run the .prg file from R run.bayesx(prg) ## End(Not run)## Not run: ## create a temporary directory for this example dir <- tempdir() prg <- file.path(dir, "demo.prg") ## generate some data set.seed(111) n <- 200 ## regressor dat <- data.frame(x = runif(n, -3, 3)) ## response dat$y <- with(dat, 1.5 + sin(x) + rnorm(n, sd = 0.6)) ## write data to dir write.table(dat, file.path(dir, "data.raw"), quote = FALSE, row.names = FALSE) ## create the .prg file writeLines(" bayesreg b dataset d d.infile using data.raw b.outfile = mcmc b.regress y = x(psplinerw2,nrknots=20,degree=3), family=gaussian predict using d b.getsample", prg) ## run the .prg file from R run.bayesx(prg) ## End(Not run)