Creates a faceted plot of two-dimensional correlation plots and
unidimensional density plots for a single mixture model.

```
plot_bivariate(
x,
variables = NULL,
sd = TRUE,
cors = TRUE,
rawdata = TRUE,
bw = FALSE,
alpha_range = c(0, 0.1),
return_list = FALSE,
...
)
```

## Arguments

- x
An object for which a method exists.

- variables
Which variables to plot. If NULL, plots all variables that
are present in the model.

- sd
Logical. Whether to show the estimated standard deviations as lines
emanating from the cluster centroid.

- cors
Logical. Whether to show the estimated correlation (standardized
covariance) as ellipses surrounding the cluster centroid.

- rawdata
Logical. Whether to plot raw data, weighted by posterior class
probability.

- bw
Logical. Whether to make a black and white plot (for print) or a
color plot. Defaults to FALSE, because these density plots are hard to read
in black and white.

- alpha_range
Numeric vector (0-1). Sets
the transparency of geom_density and geom_point.

- return_list
Logical. Whether to return a list of ggplot objects, or
just the final plot. Defaults to FALSE.

- ...
Additional arguments.

## Value

An object of class 'ggplot'.

## Author

Caspar J. van Lissa

## Examples

```
iris_sample <- iris[c(1:5, 145:150), c("Sepal.Length", "Sepal.Width")]
names(iris_sample) <- c("x", "y")
res <- mx_profiles(iris_sample, classes = 2)
#> Running mix2 with 7 parameters
#> Running mix2 with 7 parameters
plot_bivariate(res, rawdata = FALSE)
```