plotxc: Condition selector plot

In condvis: Conditional Visualization for Statistical Models

Description

Data visualisations used to select sections for ceplot.

Usage

plotxc(xc, xc.cond, name = NULL, trim = NULL, select.colour = NULL,
  select.lwd = NULL, cex.axis = NULL, cex.lab = NULL, tck = NULL,
  select.cex = 1, hist2d = NULL, fullbin = NULL, ...)

Arguments

xc	A numeric or factor vector, or a dataframe with two columns
xc.cond	Same type as xc, representing a single point in data space to highlight.
name	The variable name for xc
trim	Logical; if TRUE, long tails of continuous data are chopped off at the 5th and 95th percentiles.
select.colour	Colour to highlight xc.cond
select.lwd	Line weight to highlight xc.cond
cex.axis	Axis text scaling
cex.lab	Label text scaling
tck	Plot axis tick size
select.cex	Plot symbol size
hist2d	If TRUE, a scatterplot is visualised as a 2-D histogram. Default behaviour is to use a 2-D histogram if there are over 2,000 observations.
fullbin	A cap on the counts in a bin for the 2-D histogram, helpful with skewed data. Larger values give more detail about data density. Defaults to 25.
...	Passed to condvis:::spineplot2.

Value

Produces a plot, and returns a list containing the relevant information to update the plot at a later stage.

References

O'Connell M, Hurley CB and Domijan K (2017). “Conditional Visualization for Statistical Models: An Introduction to the condvis Package in R.”Journal of Statistical Software, 81(5), pp. 1-20. <URL:http://dx.doi.org/10.18637/jss.v081.i05>.

See Also

ceplot, plotxs.

plotxs, ceplot, condtour

Examples

## Histogram, highlighting the first case.

data(mtcars)
obj <- plotxc(mtcars[, "mpg"], mtcars[1, "mpg"])
obj$usr

## Barplot, highlighting 'cyl' = 6.

plotxc(as.factor(mtcars[, "cyl"]), 6, select.colour = "blue")

## Scatterplot, highlighting case 25.

plotxc(mtcars[, c("qsec", "wt")], mtcars[25, c("qsec", "wt")],
  select.colour = "blue", select.lwd = 1, lty = 3)

## Boxplot, where 'xc' contains one factor, and one numeric.

mtcars$carb <- as.factor(mtcars$carb)
plotxc(mtcars[, c("carb", "wt")], mtcars[25, c("carb", "wt")],
  select.colour = "red", select.lwd = 3)

## Spineplot, where 'xc' contains two factors.

mtcars$gear <- as.factor(mtcars$gear)
mtcars$cyl <- as.factor(mtcars$cyl)
plotxc(mtcars[, c("cyl", "gear")], mtcars[25, c("cyl", "gear")],
  select.colour = "red")

## Effect of 'trim'.

x <- c(-200, runif(400), 200)
plotxc(x, 0.5, trim = FALSE, select.colour = "red")
plotxc(x, 0.5, trim = TRUE, select.colour = "red")

condvis documentation built on May 2, 2019, 5:57 a.m.