R/pbgpd.R

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

pbgpd <-
function (x, y,
model = "log",
mar1 = c(0, 1, 0.1),
mar2 = c(0, 1, 0.1),
dep = 2,
a = 1/2, b = 1/2, asy = 0, p = 3,  ...)
{
    pbgpd   = NULL    
    models = c("log", "psilog", "philog", 
        "neglog", "psineglog" , "phineglog", 
        "bilog" , "negbilog"  , "ct", "taj")#, "smith", "mix")
    if (!(model %in% models))
        stop(paste("'", model, "' is an unknown model.", sep = ""))
    else {
        if (model == "log")
            pbgpd = pbgpd_log(x, y, mar1 = mar1, mar2 = mar2, dep = dep)
        if (model == "psilog")
            pbgpd = pbgpd_psilog(x, y, mar1 = mar1, mar2 = mar2, dep = dep, asy = asy, p = p)
        if (model == "philog")
            pbgpd = pbgpd_philog(x, y, mar1 = mar1, mar2 = mar2, dep = dep, asy = asy, p = p)
        if (model == "neglog")
            pbgpd = pbgpd_neglog(x, y, mar1 = mar1, mar2 = mar2, dep = dep )
        if (model == "psineglog")
            pbgpd = pbgpd_psineglog(x, y, mar1 = mar1, mar2 = mar2, dep = dep, asy = asy, p = p)
        if (model == "phineglog")
            pbgpd = pbgpd_phineglog(x, y, mar1 = mar1, mar2 = mar2, dep = dep, asy = asy, p = p)
        if (model == "bilog")
            pbgpd = pbgpd_bilog(x, y, mar1 = mar1, mar2 = mar2, dep = dep, a = a, b = b)
        if (model == "negbilog")
            pbgpd = pbgpd_negbilog(x, y, mar1 = mar1, mar2 = mar2, dep = dep, a = a, b = b)
        #if (model == "mix")
        #    pbgpd = pbgpd_mix(x, y, mar1 = mar1, mar2 = mar2)
        if (model == "ct")
            pbgpd = pbgpd_ct(x, y, mar1 = mar1, mar2 = mar2, a = a, b = b)
        if (model == "taj")
            pbgpd = pbgpd_taj(x, y, mar1 = mar1, mar2 = mar2, a = a, b = b)
        #if (model == "smith")
        #    pbgpd = pbgpd_smith(x, y, mar1 = mar1, mar2 = mar2, dep = dep)
    }
pbgpd
}