densityPlot: Plot fitted kernel densities

In overlap: Estimates of Coefficient of Overlapping for Animal Activity Patterns

Plot fitted kernel densities

Description

Fits a kernel density function to a data set and plots it.

Usage

densityPlot(A, xscale = 24, xcenter = c("noon", "midnight"),
   add = FALSE, rug = FALSE, extend = 'lightgrey',
   n.grid = 128, kmax = 3, adjust = 1, ...)

Arguments

A	a vector of times of observations in radians, ie. scaled to [0, 2\pi]. It must include at least 2 unique observations to fit a kernel density.
xscale	The scale for the x axis: 24 (the default) produces a curve with 0 to 24 hours. NA gives a scale in radians, labelled with pi.
xcenter	the center of the plot on the x axis: 'noon' (default) or 'midnight'.
add	If TRUE, the curve will be added to the existing plot. Use the same settings for xscale and xcenter as for the original plot.
rug	If TRUE, the original observations will be displayed as a rug at the bottom of the plot.
extend	If not NULL, the plot extends 3 hours before and after the main 24-hr period, and extend specifies the background colour; the plot is not extended if extend = NULL.
n.grid	Number of points at which to estimate the density for plotting; 100 is usually adequate to give a smooth-looking curve.
kmax	maximum value of k for optimal bandwidth estimation.
adjust	bandwidth adjustment (scalar).
...	Further arguments passed to the plotting functions, such as col, lty, lwd or xlab, ylab, main.

Value

Returns invisibly a data frame with x and y coordinates which can be used for further plotting or calculations; see examples.

Author(s)

Mike Meredith

Examples

# Get example data:
data(simulatedData)

# Do basic plot with defaults:
densityPlot(pigObs)

# Prettier plots:
densityPlot(pigObs, extend=NULL, lwd=2)
densityPlot(pigObs, rug=TRUE, main="Simulated data", extend='gold')
densityPlot(tigerObs, add=TRUE, rug=TRUE, col='red')
legend('topleft', c("Tiger", "Pig"), lty=1, col=c('black', 'red'), bg='white')
# Add vertical dotted lines to mark sunrise (say 05:30) and sunset (18:47):
# (times must be in hours if the x-axis is labelled in hours)
abline(v=c(5.5, 18+47/60), lty=3)

# A plot centered on midnight:
densityPlot(pigObs, xcenter = "m")
# Mark sunrise/sunset; values to the left of "00:00" are negative
# so subtract 24:
abline(v=c(5.5, (18+47/60) - 24), lty=3)

# Using object returned:
densityPlot(pigObs, rug=TRUE, lwd=3)
# Don't like the rug with lwd = 3?
pigDens <- densityPlot(pigObs, rug=TRUE)
lines(pigDens, lwd=3)

# Add shading below the curve:
pigDens <- densityPlot(pigObs, extend=NULL)
polygon(pigDens, col='skyblue') # works if density at midnight = 0
tigDens <- densityPlot(tigerObs, extend=NULL)
# Add vertices at (0,0) and (24, 0)
poly <- rbind(c(0,0), tigDens, c(24,0))
polygon(poly, col='pink', border=NA)
lines(tigDens, lwd=2)

# What proportion of the density lies between 9:00 and 15:00 hrs?
wanted <- pigDens$x > 9 & pigDens$x < 15
mean(pigDens$y[wanted]) * 6  # probability mass for the 6 hr period.

# Plotting time in radians:
densityPlot(pigObs, xscale=NA, rug=TRUE)
densityPlot(tigerObs, xscale=NA, add=TRUE, rug=TRUE, col='red')

overlap documentation built on Nov. 18, 2023, 5:09 p.m.