| Title: | Discrete Distribution Approximations |
| Version: | 1.0.3 |
| Description: | Creates discretised versions of continuous distribution functions by mapping continuous values to an underlying discrete grid, based on a (uniform) frequency of discretisation, a valid discretisation point, and an integration range. For a review of discretisation methods, see Chakraborty (2015) <doi:10.1186/s40488-015-0028-6>. |
| License: | MIT + file LICENSE |
| LazyData: | true |
| URL: | https://github.com/reconhub/distcrete |
| BugReports: | https://github.com/reconhub/distcrete/issues |
| Suggests: | knitr, rmarkdown, testthat |
| RoxygenNote: | 6.0.1 |
| VignetteBuilder: | knitr |
| NeedsCompilation: | no |
| Packaged: | 2017-11-23 12:44:36 UTC; steph |
| Author: | Steph Locke [cre], Rich FitzJohn [aut], Anne Cori [aut], Thibaut Jombart [aut] |
| Maintainer: | Steph Locke <steph@itsalocke.com> |
| Repository: | CRAN |
| Date/Publication: | 2017-11-23 13:50:05 UTC |
Discretise a distribution
Description
Discretise a distribution.
Usage
distcrete(name, interval, ..., w = 0.5, anchor = 0)
Arguments
name |
The name of a distribution function (e.g.,
|
interval |
The interval to discretise the interval onto. |
... |
Parameters to |
w |
How to weight the endpoints; must be between 0 and 1. If 0.5 then integration happens centred around the interval, if 0 floor, if 1 then ceiling. |
anchor |
Any location that is a valid |
Author(s)
Rich FitzJohn
Examples
library(distcrete)
set.seed(415)
d0 <- distcrete("gamma", 1, shape = 3, w = 0)
d0$d(1:10)
d0$p(c(.1,.5))
d0$q(c(.1,.5))
d0$r(10)