plot_univariate | R Documentation |
A scatter plot showing the relationship between estimated density ratios and individual variables.
plot_univariate(
x,
vars = NULL,
samples = "both",
logscale = TRUE,
grid = FALSE,
sample.facet = FALSE,
nrow.panel = NULL,
tol = 0.01,
...
)
x |
Density ratio object created with e.g., |
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. |
Scatter plot of density ratios and individual variables.
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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.