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Normal Distribution, Using Multiple Draws

Source: R/distributions.R
dnorm_rvec.Rd

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 dnorm(). Can be an rvec.

sd

Standard deviation. Default is 1. See 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

See also

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] -2.8 (-6.7, 0.9) 3.1 (-4.4, 11)