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

## Description

internal use only

## Usage

 `1` ```ml_mix(param, dat, mlmax = 1e+15, fixed = FALSE, ...) ```

## Arguments

 `param` `dat` `mlmax` `fixed` `...`

## Details

internal use only

## Value

internal use only

## Note

internal use only

P. Rakonczai

## References

internal use only

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48``` ```##---- 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 (param, dat, mlmax = 1e+15, fixed = FALSE, ...) { loglik = mlmax hxy = NA x = dat[, 1] y = dat[, 2] error = FALSE mux = param[1] muy = param[4] sigx = param[2] sigy = param[5] gamx = param[3] gamy = param[6] alpha = 1 mu = function(x, y) 1/x + 1/y - alpha/(x + y) dxdymu = function(x, y) -2 * alpha/(x + y)^3 if (sigx < 0 | sigy < 0) error = TRUE if (fixed == TRUE) { mux = 0 } if (error) loglik = mlmax 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)))) loglik = -sum(log(hxy)) } if (min(1 + gamx * (x - mux)/sigx) < 0) loglik = mlmax if (min(1 + gamy * (y - muy)/sigy) < 0) loglik = mlmax loglik } ```