# plot.theta: Plotting method for "theta" objects In GMCM: Fast Estimation of Gaussian Mixture Copula Models

## Description

Visualizes the chosen dimensions of the theta object graphically by the GMM density and possibly the individual gaussian components.

## Usage

 ```1 2 3``` ```## S3 method for class 'theta' plot(x, which.dims = c(1L, 2L), n.sd = qnorm(0.99), add.means = TRUE, ..., add.ellipses = FALSE) ```

## Arguments

 `x` An object of class `theta`. `which.dims` An integer vector of length 2 choosing which two dimensions to plot. `n.sd` An integer choosing the number of standard deviations in each dimension to determine the plotting window. `add.means` logical. If TRUE, dots corresponding to the means are added to the plot. `...` Arguments passed to `contour`. `add.ellipses` logical. If TRUE, ellipses outlining a 95% confidence regions for each component are added in the bivariate multivariate distribution defined by theta and `which.dims`.

## Value

Plots via the `contour` function. Invisibly returns a list with x, y, z coordinates that is passed to contour.

## Author(s)

Anders Ellern Bilgrau <anders.ellern.bilgrau@gmail.com>

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```set.seed(5) theta <- rtheta(d = 3, m = 2) ## Not run: plot(theta) plot(theta, col = "blue", asp = 1, add.means = FALSE) plot(theta, col = "blue", asp = 1, add.means = TRUE) plot(theta, which.dims = c(3L, 2L), asp = 1) ## End(Not run) plot(theta, asp = 1, n.sd = 3, add.ellipses = TRUE, nlevels = 40, axes = FALSE, xlab = "Dimension 1", ylab = "Dimension 2") ```

GMCM documentation built on Nov. 6, 2019, 1:08 a.m.