# dibivar: Probability distribution function values based the... In BivarP: Estimating the Parameters of Some Bivariate Distributions

## Description

Computes the probability distribution function values based the Archimedean copula on the grid of `x` and `y` vectors.

## Usage

 `1` ```dibivar(x, y, par, afa, rodina, fam) ```

## Arguments

 `x` numeric vector `y` numeric vector `par` vector of this values: `par[1]`, `par[3]` are `shape` for the Weibull and the Gamma distributions or `mean` for the Normal distribution or `meanlog` for the Lognormal ditribution. par[2], par[4] are `scale` for the Weibull and the Gamma distributions or `sd` for the Normal distribution or `sdlog` for the Lognormal ditribution. `afa` copula parameter `rodina` vector of length 2 of names of the marginal distributions. Distributions can be "weibull", "gamma", "norm", "lnorm". "norm" is the name for the Normal distribution. "lnorm" is the name for the Lognormal distribution. `fam` name of copula. It can be "gumbel", "clayton", "frank".

## Value

Returns an array of values of the probability distribution function.

Josef Brejcha

## Examples

 ```1 2 3 4 5 6``` ```x <- seq(0, 100, 5) y <- seq(0, 100, 4) pxy <- dibivar(x, y, c(1.5, 50, 1.3, 50), 5, c("weibull", "weibull"), "gumbel") colnames(pxy) <- x rownames(pxy) <- y contour(y, x, pxy, xlab="y", ylab="x") ```

BivarP documentation built on May 29, 2017, 7:13 p.m.