plot_bivariate {tidySEM} | R Documentation |
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 )
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. |
An object of class 'ggplot'.
Caspar J. van Lissa
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) plot_bivariate(res, rawdata = FALSE)