| snig {fBasics} | R Documentation |
Density, distribution function, quantile function and random generation for the standardized normal inverse Gaussian distribution.
dsnig(x, zeta = 1, rho = 0, log = FALSE) psnig(q, zeta = 1, rho = 0) qsnig(p, zeta = 1, rho = 0) rsnig(n, zeta = 1, rho = 0)
zeta, rho |
shape parameter |
log |
a logical flag by default |
n |
number of observations. |
p |
a numeric vector of probabilities. |
x, q |
a numeric vector of quantiles. |
The random deviates are calculated with the method described by Raible (2000).
All values for the *snig functions are numeric vectors:
d* returns the density,
p* returns the distribution function,
q* returns the quantile function, and
r* generates random deviates.
All values have attributes named "param" listing
the values of the distributional parameters.
Diethelm Wuertz.
## snig -
set.seed(1953)
r = rsnig(5000, zeta = 1, rho = 0.5)
plot(r, type = "l", col = "steelblue",
main = "snig: zeta=1 rho=0.5")
## snig -
# Plot empirical density and compare with true density:
hist(r, n = 50, probability = TRUE, border = "white", col = "steelblue")
x = seq(-5, 5, length = 501)
lines(x, dsnig(x, zeta = 1, rho = 0.5))
## snig -
# Plot df and compare with true df:
plot(sort(r), (1:5000/5000), main = "Probability", col = "steelblue")
lines(x, psnig(x, zeta = 1, rho = 0.5))
## snig -
# Compute Quantiles:
qsnig(psnig(seq(-5, 5, 1), zeta = 1, rho = 0.5), zeta = 1, rho = 0.5)