densityratio (version 0.2.1)

plot_univariate: Scatter plot of density ratios and individual variables

Description

A scatter plot showing the relationship between estimated density ratios and individual variables.

Usage

plot_univariate(
  x,
  vars = NULL,
  samples = "both",
  logscale = TRUE,
  grid = FALSE,
  sample.facet = FALSE,
  nrow.panel = NULL,
  tol = 0.01,
  ...
)

Value

Scatter plot of density ratios and individual variables.

Arguments

x

Density ratio object created with e.g., kliep(), ulsif(), or naive()

vars

Character vector of variable names to be plotted.

samples

Character string indicating whether to plot the 'numerator', 'denominator', or 'both' samples. Default is 'both'.

logscale

Logical indicating whether to plot the density ratio estimates on a log scale. Default is TRUE.

grid

Logical indicating whether output should be a list of individual plots ("individual"), or one facetted plot with all variables ("assembled"). Defaults to "individual".

sample.facet

Logical indicating whether to facet the plot by sample, i.e, showing plots separate for each sample, and side to side. Defaults to FALSE.

nrow.panel

Integer indicating the number of rows in the assembled plot. If NULL, the number of rows is automatically calculated.

tol

Numeric indicating the tolerance: values below this value will be set to the tolerance value, for legibility of the plots

...

Additional arguments passed to the predict() function.

Examples

set.seed(123)
# Fit model
dr <- ulsif(numerator_small, denominator_small)
# Inspect model object
dr
# Obtain summary of model object
summary(dr)
# Plot model object
plot(dr)
# Plot density ratio for each variable individually
plot_univariate(dr)
# Plot density ratio for each pair of variables
plot_bivariate(dr)
# Predict density ratio and inspect first 6 predictions
head(predict(dr))
# Fit model with custom parameters
ulsif(numerator_small, denominator_small, sigma = 2, lambda = 2)