plotmcd | R Documentation |

Plots the probability density of the multivariate Cauchy distribution with 2 variables
with location parameter `mu`

and scatter matrix `Sigma`

.

```
plotmcd(mu, Sigma, xlim = c(mu[1] + c(-10, 10)*Sigma[1, 1]),
ylim = c(mu[2] + c(-10, 10)*Sigma[2, 2]), n = 101,
xvals = NULL, yvals = NULL, xlab = "x", ylab = "y",
zlab = "f(x,y)", col = "gray", tol = 1e-6, ...)
```

`mu` |
length 2 numeric vector. |

`Sigma` |
symmetric, positive-definite square matrix of order 2. The scatter matrix. |

`xlim` , `ylim` |
x-and y- limits. |

`n` |
A one or two element vector giving the number of steps in the x and y grid, passed to |

`xvals` , `yvals` |
The values at which to evaluate |

`xlab` , `ylab` , `zlab` |
The axis labels. |

`col` |
The color to use for the plot. See |

`tol` |
tolerance (relative to largest variance) for numerical lack of positive-definiteness in Sigma, for the estimation of the density. see |

`...` |
Additional arguments to pass to |

Returns invisibly the probability density function.

Pierre Santagostini, Nizar Bouhlel

N. Bouhlel, D. Rousseau, A Generic Formula and Some Special Cases for the Kullback–Leibler Divergence between Central Multivariate Cauchy Distributions. Entropy, 24, 838, July 2022. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3390/e24060838")}

`dmcd`

: probability density of a multivariate Cauchy density

`contourmcd`

: contour plot of a bivariate Cauchy density.

`plot3d.function`

: plot a function of two variables.

```
mu <- c(1, 4)
Sigma <- matrix(c(0.8, 0.2, 0.2, 0.2), nrow = 2)
plotmcd(mu, Sigma)
```

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