| get.corr.key | R Documentation | 
A function for adding correlation key legends to scatterplots.
get.corr.key(
	x, 
	y, 
	label.items = c("spearman", "spearman.p"), 
	x.pos = 0.03, 
	y.pos = 0.97, 
	key.corner = NULL, 
	key.cex = 1, 
	key.title = NULL, 
	title.cex = 1, 
	alpha.background = 0,
	num.decimals = 2,
        border = 'white'
	)
| x | A vector of values | 
| y | Another vector of values with the same length as x | 
| label.items | A vector of things to include in the key. Any combination of the following can be used. c("spearman","pearson","kendall","beta0", beta1,"spearman.p","pearson.p","kendall.p","beta1.p", "beta.robust", "beta.robust.p"). "all" is an alternative to the full list. | 
| x.pos | Horizontal position of the key corner | 
| y.pos | Vertical position of the key corner | 
| key.corner | The corner of the key defaults to the closest corner of the plot. This helps overcome some variable character and row sizing. | 
| key.cex | Specifies the size of font for the key, defaults to 1. | 
| key.title | The title of the key. Defaults to NULL | 
| title.cex | The size of the key title. Defaults to 1 | 
| alpha.background | A value from 0 to 1 indicating the transparency of the legend box. | 
| num.decimals | Number of decimal places to keep for spearman, pearson and kendall correlations. Defaults to 2. | 
| border | Adds border around the key with the color specified, alpha background cannot be 0. Defaults to White. | 
Returns a key in the format specified in the xyplot documentation.
Daryl Waggott
xyplot, plotmath
# create some temporary data
tmp.data <- data.frame(
    x = c(
        runif(n = 15, min =  0, max =  20),
        runif(n = 15, min = 80, max = 100),
        runif(n = 70, min =  0, max = 100)
        ),
    y = c(
        runif(n = 15, min =  0, max =  20),
        runif(n = 15, min = 80, max = 100),
        runif(n = 70, min =  0, max = 100)
        )
    );
# a simple scatterplot with correlation key
BoutrosLab.plotting.general::create.scatterplot(
    formula = y ~ x,
    data = tmp.data,
    # filename = tempfile(pattern = 'get.corr.key-scatterplot', fileext = '.tiff'),
    xlab.label = 'X Axis Title',
    ylab.label = 'Y Axis Title',
    xlimits = c(0,100),
    ylimits = c(0,100),
    xat = seq(0,100,25),
    yat = seq(0,100,25),
    add.axes = FALSE,
    key = BoutrosLab.plotting.general::get.corr.key(
        tmp.data$y,
        tmp.data$x,
        label.items = c('spearman', 'spearman.p', 'kendall', 'beta1', 'beta1.p')
        )
    );
# compare beta1 vs a robust estimate of the slope
# add an outlier
tmp.data <- rbind(tmp.data, c(2000,100));
BoutrosLab.plotting.general::create.scatterplot(
    formula = y ~ x,
    data = tmp.data,
    # filename = tempfile(pattern = 'get.corr.key.robust-scatterplot', fileext = '.tiff'),
    xlab.label = 'X Axis Title',
    ylab.label = 'Y Axis Title',
    xlimits = c(0,100),
    ylimits = c(0,100),
    xat = seq(0,100,25),
    yat = seq(0,100,25),
    add.axes = FALSE,
    key = BoutrosLab.plotting.general::get.corr.key(
        tmp.data$y,
        tmp.data$x,
        label.items = c('beta1', 'beta1.robust','beta1.p','beta1.robust.p')
        )
    );
# see create.scatterplot for an example of creating multiple keys using legends
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