The Normal Distribution, Using Multiple Draws

Density, distribution function, quantile function and random generation for the normal distribution, modified to work with rvecs.

Usage

dnorm_rvec(x, mean = 0, sd = 1, log = FALSE)

pnorm_rvec(q, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)

qnorm_rvec(p, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)

rnorm_rvec(n, mean = 0, sd = 1, n_draw = NULL)

Arguments

x: Quantiles. Can be an rvec.
mean: Mean of distribution. Default is 0. See stats::dnorm(). Can be an rvec.
sd: Standard deviation. Default is 1. See stats::dnorm(). Can 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_draw is supplied, then an rvec
Otherwise an ordinary R vector.

Details

Functions dnorm_rvec(), pnorm_rvec(), pnorm_rvec() and rnorm_rvec() work like base R functions dnorm(), pnorm(), qnorm(), and rnorm(), except that they accept rvecs as inputs. If any input is an rvec, then the output will be too. Function rnorm_rvec() also returns an rvec if a value for n_draw is supplied.

dnorm_rvec(), pnorm_rvec(), pnorm_rvec() and rnorm_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(3.1, -5.4),
               c(0.1, 2.3)))
dnorm_rvec(x)
#> <rvec_dbl<2>[2]>
#> [1] 0.003267,0.0000001857 0.397,0.02833        
pnorm_rvec(x)
#> <rvec_dbl<2>[2]>
#> [1] 0.999,0.00000003332 0.5398,0.9893      

rnorm_rvec(n = 2,
           mean = c(-3, 3),
           sd = c(2, 4),
           n_draw = 1000)
#> <rvec_dbl<1000>[2]>
#> [1] -3.1 (-6.8, 0.59) 3 (-5.3, 11)