Orcs (version 1.2.3)

compareDistributions: Compare Two Density Distributions Side by Side

Description

This function will produce a plot of two density functions displayed side by side.

Usage

compareDistributions(
  left,
  right,
  add.spread = TRUE,
  print.stats = TRUE,
  xlim = NULL,
  ylim = NULL,
  clrs = c("purple", "lightblue"),
  xlab = "density",
  ylab = "value",
  ...
)

Value

A trellis object.

Arguments

left

numeric vector.

right

numeric vector.

add.spread

logical, whether to plot the spread (q25 to q75 and the median).

print.stats

logical, whether to print summary statistics for each distribution.

xlim, ylim

numeric axis limits, see lattice::xyplot().

clrs

A character vector of length 2 specifying the colors for the filled density regions.

xlab, ylab

character axis labels, see graphics::plot().

...

Additional arguments passed to stats::density().

Author

Tim Appelhans

Examples

compareDistributions(rnorm(1000, 2, 3), rnorm(1000, -5, 1))
compareDistributions(rnorm(1000, 2, 3), rnorm(1000, -5, 1), 
                     add.spread = FALSE)
compareDistributions(rnorm(1000, 2, 3), rnorm(1000, -5, 1), 
                     add.spread = TRUE, clrs = c("red", "brown"))
compareDistributions(rnorm(1000, 2, 5), rnorm(1000, -5, 4), 
                     print.stats = FALSE, add.spread = FALSE)
                     
## pass additional parameters to stats::density() 
compareDistributions(rnorm(1000, 2, 5), rnorm(1000, -5, 4), 
                     print.stats = FALSE, add.spread = FALSE, bw = 5)
compareDistributions(rnorm(1000, 2, 5), rnorm(1000, -5, 4), 
                     print.stats = FALSE, add.spread = FALSE, bw = 8,
                     kernel = "rectangular")
compareDistributions(rnorm(1000, 2, 5), rnorm(1000, -5, 4), 
                     print.stats = FALSE, add.spread = TRUE, bw = 8,
                     n = 3)
compareDistributions(rnorm(1000, 2, 5), rnorm(1000, -5, 4), 
                     print.stats = TRUE, add.spread = TRUE, bw = 0.1)
compareDistributions(rnorm(1000, 2, 5), rnorm(1000, -5, 4), 
                     print.stats = TRUE, add.spread = TRUE, bw = 0.5)