distfree.cr {distfree.cr} | R Documentation |
Constructs empirical confidence regions for bivariate data based on the method proposed by Zhiqiu Hu and Rong-cai Yang(2013) <doi:10.1371/journal.pone.0081179.g001>.
distfree.cr(x, y, alpha = 0.05, alpha.min.diff = 0.5/NROW(x), nknots = 40,
xlab = deparse(substitute(x)), ylab = deparse(substitute(y)),
col = c("red", "black", "gray"), draw = T)
x |
numeric vector, of dimensions nobs * 1. If a data frame or a two-column numeric matrix of x and y is supplied here, the second option |
y |
numeric vector, of dimensions nobs * 1. This option needs to be ignored if users provided both x and y in the first option of the function. |
alpha |
Significant level. By default |
alpha.min.diff |
minimum difference is allowed for calculating confidence region. This option is not suggested for most users. The default value is set to be |
nknots |
number of knots that will be used to enclose the confidence region. The default value |
xlab |
define the label of x axis of the plot. |
ylab |
define the label of y axis of the plot. |
col |
define colors of the scatter points and lines of the plot. The default setting |
draw |
a logical indicator. Users may disable plotting by setting the option to |
This function constructs a distribution-free confidence region based on the method proposed by Zhiqiu Hu and Rong-cai Yang.
alpha.realized |
Realized-alpha, which is defined as the proportion of the total points outside the confidence region. |
polygon |
'data.frame' of x,y providing the apexes of the lines. |
polygon.smooth1 |
'data.frame' of x,y providing the apexes of the smoothed polygon 1. |
polygon.smooth2 |
'data.frame' of x,y providing the apexes of the smoothed polygon 2. |
data |
'data.frame', of dimension nobs * 3, the first two columns are input data of x and y values and the third column |
alpha,xlab,ylab,col |
values assigned by users. |
A smooth confidence region can be achieved by setting up a big number for input variable nknots, and this in turn requires large sample sizes.
Zhiqiu Hu and Rong-cai Yang
library(distfree.cr)
dat=data.frame(x=c(rnorm(3000), rnorm(3000, mean=1, sd=2.5)),
y=c(rnorm(3000), rnorm(3000, mean=1, sd=2.5)))
pt=distfree.cr(dat, draw=TRUE, alpha=0.05)
pt=distfree.cr(x=dat$x, y=dat$y, draw=FALSE)
plot(pt)