pcsn: The cumulative distribution function
In csn: Closed Skew-Normal Distribution

Description Usage Arguments Details Value See Also Examples

The cumulative distribution function of the closed-skew normal distribution

1	pcsn(x, mu, sigma, gamma, nu, delta)

`x`	this is either a vector of length `n` or a matrix with `n` columns, where `n=ncol(sigma)`, giving the coordinates of the point(s) where the cdf must be evaluated
`mu`	a numeric vector representing the location parameter of the distribution; it must be of length `n`, as defined above
`sigma`	a positive definite matrix representing the scale parameter of the distribution; a vector of length 1 is also allowed
`gamma`	a matrix representing the skewness parameter of the distribution; a vector of length 1 is also allowed
`nu`	a numeric vector allows for closure with conditional densities; it must be of length `q`, as defined above
`delta`	a positive definite matrix allows for closure with the marginal densities; a vector of length 1 is also allowed

Function pcsn makes use of pmvnorm from package mvtnorm

pcsn returns a vector of cdf values

pmvnorm

x1 <- seq(4,6,by = 0.1)
x2 <- x1+sin(x1)
x3 <- x1-cos(x1)
x <- cbind(x1,x2,x3)
mu <- c(1,2,3)
sigma <- matrix(c(2,-1,0,-1,2,-1,0,-1,2),3)
gamma <- matrix(c(0,1,0,2,2,3),2,3)
nu <- c(1,3)
delta <- matrix(c(1,1,1,2),2)
pcsn(6,5,9,1,0,0.05)
pcsn(c(3,4,5),mu,sigma,gamma,nu,delta)
pcsn(x,mu,sigma,gamma,nu,delta)