Density, distribution function, quantile function and random generation for the Beta distribution, modified to work with rvecs.
Usage
dbeta_rvec(x, shape1, shape2, ncp = 0, log = FALSE)
pbeta_rvec(q, shape1, shape2, ncp = 0, lower.tail = TRUE, log.p = FALSE)
qbeta_rvec(p, shape1, shape2, ncp = 0, lower.tail = TRUE, log.p = FALSE)
rbeta_rvec(n, shape1, shape2, ncp = 0, n_draw = NULL)Arguments
- x
Quantiles. Can be an rvec.
- shape1, shape2
Parameters for beta distribution. Non-negative. See
stats::dbeta(). Can be an rvecs.- ncp
Non-centrality parameter. Default is
0. Cannot be an rvec.- log, log.p
Whether to return results on a log scale. Default is
FALSE. Cannot be an rvec.- q
Quantiles. Can be an rvec.
- lower.tail
Whether to return \(P[X \le x]\), as opposed to \(P[X > x]\). Default is
TRUE. Cannot be an rvec.- p
Probabilities. Can be an rvec.
- n
The length of random vector being created. Cannot be an rvec.
- n_draw
Number of random draws in the random vector being created. Cannot be an rvec.
Value
If any of the arguments are rvecs, or if a value for
n_drawis supplied, then an rvecOtherwise an ordinary R vector.
Details
Functions dbeta_rvec(), pbeta_rvec(),
pbeta_rvec() and rbeta_rvec() work like
base R functions dbeta(), pbeta(),
qbeta(), and rbeta(), except that
they accept rvecs as inputs. If any
input is an rvec, then the output will be too.
Function rbeta_rvec() also returns an
rvec if a value for n_draw is supplied.
dbeta_rvec(), pbeta_rvec(),
pbeta_rvec() and rbeta_rvec()
use tidyverse
vector recycling rules:
Vectors of length 1 are recycled
All other vectors must have the same size
Examples
x <- rvec(list(c(0, 0.25),
c(0.5, 0.99)))
dbeta_rvec(x, shape1 = 1, shape2 = 1)
#> <rvec_dbl<2>[2]>
#> [1] 1,1 1,1
pbeta_rvec(x, shape1 = 1, shape2 = 1)
#> <rvec_dbl<2>[2]>
#> [1] 0,0.25 0.5,0.99
rbeta_rvec(n = 2,
shape = 1:2,
shape2 = 1,
n_draw = 1000)
#> <rvec_dbl<1000>[2]>
#> [1] 0.53 (0.025, 0.98) 0.71 (0.17, 0.99)