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

Description Usage Arguments Details Value Note Author(s) References See Also Examples

internal use only

1	dbgpd_mix(x, y, mar1 = c(0, 1, 0.1), mar2 = c(0, 1, 0.1), ...)

`x`
`y`
`mar1`
`mar2`
`...`

internal use only

P. Rakonczai

internal use only

##---- 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), ...) 
{
    mu = function(x, y) 1/x + 1/y - alpha/(x + y)
    dxdymu = function(x, y) -2 * alpha/(x + y)^3
    param = as.numeric(c(mar1, mar2))
    mux = param[1]
    muy = param[4]
    sigx = param[2]
    sigy = param[5]
    gamx = param[3]
    gamy = param[6]
    alpha = 1
    hxy = NULL
    error = FALSE
    if (sigx < 0 | sigy < 0) 
        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)
        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)
        c0 = -mu(tx0, ty0)
        hxy = 1/c0 * dxdymu(tx, ty) * dtx * dty
        hxy = as.numeric(hxy * (1 - ((x < 0) * (y < 0))))
    }
    else stop("invalid parameter(s)")
    hxy
  }