pbgpd_psineglog: internal

In mgpd: mgpd: Functions for multivariate generalized Pareto distribution (MGPD of Type II)

Description

internal use only

Usage

pbgpd_psineglog(x, y, mar1 = c(0, 1, 0.1), mar2 = c(0, 1, 0.1), dep = 1.5, asy = 0, p = 3, ...)

Arguments

x
y
mar1
mar2
dep
asy
p
...

Details

internal use only

Value

internal use only

Note

internal use only

Author(s)

P. Rakonczai

References

internal use only

See Also

internal use only

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (x, y, mar1 = c(0, 1, 0.1), mar2 = c(0, 1, 0.1), dep = 1.5, 
    asy = 0, p = 3, ...) 
{
    A1 = expression(1 - (x^(-alpha) + (1 - x)^(-alpha))^(-1/alpha))
    fi1 = expression(c * t^a * (1 - t)^a + t)
    d1A1 = D(A1, "x")
    d2A1 = D(d1A1, "x")
    A = function(x, alpha) eval({
        x <- x
        alpha <- alpha
        A1
    })
    d1A = function(x, alpha) eval({
        x <- x
        alpha <- alpha
        d1A1
    })
    d2A = function(x, alpha) eval({
        x <- x
        alpha <- alpha
        d2A1
    })
    d1fi1 = D(fi1, "t")
    d2fi1 = D(d1fi1, "t")
    fi = function(t, c, a) eval({
        t <- t
        c <- c
        a <- a
        fi1
    })
    d1fi = function(t, c, a) eval({
        t <- t
        c <- c
        a <- a
        d1fi1
    })
    d2fi = function(t, c, a) eval({
        t <- t
        c <- c
        a <- a
        d2fi1
    })
    Afi = function(t, alpha, c, a) A(fi(t, c, a), alpha)
    d1Afi = function(t, alpha, c, a) d1A(fi(t, c, a), alpha) * 
        d1fi(t, c, a)
    d2Afi = function(t, alpha, c, a) d2A(fi(t, c, a), alpha) * 
        (d1fi(t, c, a))^2 + d1A(fi(t, c, a), alpha) * d2fi(t, 
        c, a)
    mu = function(x, y, alpha, c, a) (1/x + 1/y) * Afi(x/(x + 
        y), alpha, c, a)
    param = as.numeric(c(mar1, mar2, dep, asy, p))
    mux = param[1]
    muy = param[4]
    sigx = param[2]
    sigy = param[5]
    gamx = param[3]
    gamy = param[6]
    alpha = param[7]
    asy = param[8]
    p = param[9]
    hxy = NULL
    error = FALSE
    xx = seq(0, 1, 0.01)
    d2Axx = d2Afi(xx, alpha, asy, p)
    d2Axx[d2Axx == -Inf] = NA
    if (min(d2Axx, na.rm = TRUE) < 0) 
        error = TRUE
    if (sigx < 0 | sigy < 0 | alpha < 0 | alpha > 6) 
        error = TRUE
    if (!error) {
        tx = (1 + gamx * (x - mux)/sigx)^(1/gamx)
        ty = (1 + gamy * (y - muy)/sigy)^(1/gamy)
        tx0 = (1 + gamx * (-mux)/sigx)^(1/gamx)
        ty0 = (1 + gamy * (-muy)/sigy)^(1/gamy)
        c0 = -mu(tx0, ty0, alpha, asy, p)
        Hxy = 1/c0 * (mu(tx, ty, alpha, asy, p) - mu(pmin(tx, 
            rep(tx0, length(tx))), pmin(ty, rep(ty0, length(tx))), 
            alpha, asy, p))
    }
    else stop("invalid parameter(s)")
    Hxy
  }

mgpd documentation built on May 2, 2019, 9:39 a.m.