normal: GPU Normal Distribution

In gmatrix: GPU Computing in R

Description

Density, distribution function, quantile function and random generation for the normal distribution with mean equal to mean and standard deviation equal to sd. All functions performed on the GPU.

Usage

gdnorm(x, mean = 0, sd = 1, log = FALSE, type = "d")
grnorm(n, mean = 0, sd = 1, type = "d")
gqnorm(q, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE,
       warn = TRUE, type = "d")
gpnorm(p, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE,
       warn = TRUE, type = "d")

Arguments

x,q	vector of quantiles
p	vector of probabilities
n	number of observations
mean	vector of means
sd	vector of standard deviations
log, log.p	logical; if TRUE, probabilities p are given as log(p)
lower.tail	logical; if TRUE (default), probabilities are P[X < x] otherwise, P[X > x].
warn	logical; if FALSE then additional warnings are disabled.
type	specify the type; may be "double", "single" (or short form "d" or "s")

Details

Very similar to the R stats functionality. However, gqnorm and gpnorm are implement currently in a way that is NOT numerically precise in the deep tails. Future releases may fix this problem.

Value

gdnorm gives the density, gpnorm gives the distribution function, gqnorm gives the quantile function, and grnorm generates random deviates.

Author(s)

Nathan Morris

See Also

dnorm

Examples

myRndNums1 = grnorm(100) #standard normals
myRndNums2 = grnorm(100, mean=c(1,2), sd=c(1,2,4,6))

gmatrix documentation built on May 29, 2017, 2:20 p.m.