dist-snorm: Skew normal distribution

snormR Documentation

Skew normal distribution

Description

Functions to compute density, distribution function, quantile function and to generate random variates for the skew normal distribution.

Usage

dsnorm(x, mean = 0, sd = 1, xi = 1.5, log = FALSE)
psnorm(q, mean = 0, sd = 1, xi = 1.5)
qsnorm(p, mean = 0, sd = 1, xi = 1.5)
rsnorm(n, mean = 0, sd = 1, xi = 1.5)

Arguments

x, q

a numeric vector of quantiles.

p

a numeric vector of probabilities.

n

the number of observations.

mean

location parameter.

sd

scale parameter.

xi

skewness parameter.

log

a logical; if TRUE, densities are given as log densities.

Details

dsnorm computed the density, psnorm the distribution function, qsnorm the quantile function, and rsnorm generates random deviates.

Value

numeric vector

Author(s)

Diethelm Wuertz for the Rmetrics R-port

References

Fernandez C., Steel M.F.J. (2000); On Bayesian Modelling of Fat Tails and Skewness, Preprint, 31 pages.

See Also

snormFit (fit), snormSlider (visualize),

sstd (skew Student-t), sged (skew GED)

Examples

## snorm -
   # Ranbdom Numbers:
   par(mfrow = c(2, 2))
   set.seed(1953)
   r = rsnorm(n = 1000)
   plot(r, type = "l", main = "snorm", col = "steelblue")
   
   # Plot empirical density and compare with true density:
   hist(r, n = 25, probability = TRUE, border = "white", col = "steelblue")
   box()
   x = seq(min(r), max(r), length = 201)
   lines(x, dsnorm(x), lwd = 2)
   
   # Plot df and compare with true df:
   plot(sort(r), (1:1000/1000), main = "Probability", col = "steelblue",
     ylab = "Probability")
   lines(x, psnorm(x), lwd = 2)
   
   # Compute quantiles:
   round(qsnorm(psnorm(q = seq(-1, 5, by = 1))), digits = 6)

fGarch documentation built on Nov. 10, 2022, 5:48 p.m.