The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

rvec

R-CMD-check Lifecycle: experimental Codecov test coverage CRAN status

Tools for working with random draws, including draws from a simulation or Bayesian analysis. The main data structure is an rvec, which holds multiple draws but which behaves (mainly) like a standard R vector.

Installation

install.packages("rvec")                            ## CRAN version
devtools::install_github("bayesiandemography/rvec") ## development version

Example

library(rvec, warn.conflicts = FALSE)
library(dplyr, warn.conflicts = FALSE)

Create an rvec.

x <- rvec(rbind(c(10, 11),
                c(100, 101),
                c(1000, 1001)))
x
#> <rvec_dbl<2>[3]>
#> [1] 10,11     100,101   1000,1001

Perform arithmetic on it.

x + 1
#> <rvec_dbl<2>[3]>
#> [1] 11,12     101,102   1001,1002

Put it in a tibble.

df <- tibble(g = c(1, 2, 1), x)
df
#> # A tibble: 3 × 2
#>       g         x
#>   <dbl> <rdbl<2>>
#> 1     1     10,11
#> 2     2   100,101
#> 3     1 1000,1001

Manipulate it in a tibble.

df %>%
  group_by(g) %>%
  count(wt = x)
#> # A tibble: 2 × 2
#> # Groups:   g [2]
#>       g         n
#>   <dbl> <rdbl<2>>
#> 1     1 1010,1012
#> 2     2   100,101

Summarise it.

draws_mean(x)
#> [1]   10.5  100.5 1000.5

Other packages for working with random draws

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.