dbgpd_negbilog: internal

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

Description

internal use only

Usage

dbgpd_negbilog(x, y, mar1 = c(0, 1, 0.1), mar2 = c(0, 1, 0.1), a = 1/2, b = 1/2, ...)

Arguments

x
y
mar1
mar2
a
b
...

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), a = 1/2, 
    b = 1/2, ...) 
{
    param = as.numeric(c(mar1, mar2, -a, -b))
    mux = param[1]
    muy = param[4]
    sigx = param[2]
    sigy = param[5]
    gamx = param[3]
    gamy = param[6]
    a = param[7]
    b = param[8]
    hxy = NULL
    error = FALSE
    if (sigx < 0 | sigy < 0 | a > 0 | b > 0) 
        error = TRUE
    if (!error) {
        hxy = NA
        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)
        dtx = (1/sigx) * pmax((1 + gamx * (x - mux)/sigx), 0)^(1/gamx - 
            1)
        dty = (1/sigy) * pmax((1 + gamy * (y - muy)/sigy), 0)^(1/gamy - 
            1)
        w = tx/(tx + ty)
        l = length(w)
        gma1 = rep(NA, l)
        for (i in 1:l) {
            eqn = function(z) (1 - a) * (1 - w[i]) * (1 - z)^b - 
                (1 - b) * w[i] * z^a
            if (w[i] == 0) 
                gma1[i] <- 0
            else if (w[i] == 1) 
                gma1[i] <- 1
            else gma1[i] <- uniroot(eqn, lower = 0, upper = 1, 
                tol = .Machine$double.eps^0.5)$root
        }
        hdens = function(w, gma = gma1) -((1 - a) * (1 - gma) * 
            gma^(1 - a))/((1 - w) * w^2 * ((1 - gma) * a + gma * 
            b))
        dxdymu = function(x1, y1) -(x1 + y1)^(-3) * hdens(x1/(x1 + 
            y1))
        c0 = log(pbvevd(c(0, 0), model = "negbilog", mar1 = c(mux, 
            sigx, gamx), mar2 = c(muy, sigy, gamy), alpha = (-a), 
            beta = (-b)))
        hxy = 1/c0 * dxdymu(tx, ty) * dtx * dty
        hxy = as.numeric(hxy * (1 - ((x < 0) * (y < 0))))
    }
    else stop("invalid parameter(s)")
    hxy
  }

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