qqnorm2 {Ecfun} | R Documentation |
Normal Probability Plot with Multiple Symbols
Description
Create a normal probability plot with one
line and different symbols for the values of
another variable, z
.
qqnorm2
produces an object of class
qqnorm2
, whose plot method produces
the plot.
To create a normal normal probability plots
with multiple lines, see qqnorm2t
or qqnorm2s:x
.
-
qqnorm2s
produces a plot with multiple lines specified either by different names in a character vectory
or by differentdata.frame
s in a listdata.
, with different points labeled according to the different levels ofz
. -
qqnorm2t
produces a plot with multiple lines withy
split on different levels ofx
, optionally with different points labeled according to different levels ofz
.
Usage
qqnorm2(y, z, plot.it=TRUE, datax=TRUE, pch=NULL,
...)
## S3 method for class 'qqnorm2'
plot(x, y, ...)
## S3 method for class 'qqnorm2'
lines(x, ...)
## S3 method for class 'qqnorm2'
points(x, ...)
Arguments
y |
For For |
z |
A variable to indicate different plotting symbols. NOTE: Otherwise, |
plot.it |
logical: Should the result be plotted? |
datax |
The |
x |
an object of class |
pch |
a named vector of the plotting symbols to
be used with names corresponding to the
levels of z. If Otherwise, if Or if NOTE: *** Otherwise, by default, |
... |
Optional arguments. For For |
Details
For qqnorm2
:
qq1. q2 <- qqnorm(y, datax=datax, ...)
qq2. q2[["z"]] <- z
qq3. q2[["pch"]]
gets whatever
pch
decodes to.
qq4
. Silently
return(list(x, y, z, pch, ...))
, where
x
and y
are as returned by
qqnorm
in step 1 above. If
pch
is not provided and z
is not
logical or positive integers, then z
itself will be plotted and pch
will not be
in the returned list.
For plot.qqnorm2
:
plot1. plot(x\$x, x\$y, type="n", ...)
with ...
taking precedence over x
,
where the same plot argument appears in both.
plot2. if(type %in%
c('l', 'b', 'c', 'o'))
lines(x\$x, x\$y, ...)
plot3. if(type %in% c('p', 'b', 'o')):
if(is.null(x\$z))points(x\$x, x\$y, ...)
else if(is.logical(x\$z))
points(x\$x, x\$y, pch=x\$pch[x\$z], ...)
else if(is.numeric(x\$z) &&
(min(z0 <- round(x\$z))>0) &&
(max(abs(x\$z-z0))<10*.Machine\$double.eps))
points(x\$x, x\$y, pch=x\$pch[x\$z], ...)
else text(x\$x, x\$y, x\$z, ...)
For lines.qqnorm2
lines1.
if(type != 'p')lines(x$x, x$y, ...)
;
lines2. if(type %in%
c('p', 'b', 'o'))
if(is.null(pch))text(x\$x, x\$y, x\$z, ...)
else if(is.character(pch))
text(x\$x, x\$y, x\$pch[x\$z], ...)
else points(x\$x, x\$y, pch=x\$pch[x\$z], ...)
For points.qqnorm2
points1.
if(type %in% c('p', 'b', 'o'))
if(is.null(pch))text(x\$x, x\$y, x\$z, ...)
else if(is.character(pch))
text(x\$x, x\$y, x\$pch[x\$z], ...)
else points(x\$x, x\$y, pch=x\$pch[x\$z], ...)
points2. if(!(type %in% c('p', 'n')))
lines(x$x, x$y, ...)
Value
qqnorm2
returns a list with
components, x, y, z
, and pch
.
Author(s)
Spencer Graves
See Also
qqnorm
, qqnorm2s
,
qqnorm2t
plot
points
lines
Examples
##
## a simple test data.frame to illustrate the plot
## but too small to illustrate qqnorm concepts
##
tstDF <- data.frame(y=1:3, z1=1:3, z2=c(TRUE, TRUE, FALSE),
z3=c('tell', 'me', 'why'), z4=c(1, 2.4, 3.69) )
# plotting symbols circle, triangle, and "+"
qn1 <- with(tstDF, qqnorm2(y, z1))
# plotting symbols "x" and "o"
qn2 <- with(tstDF, qqnorm2(y, z2))
# plotting with "-" and "+"
qn. <- with(tstDF, qqnorm2(y, z2, pch=c('FALSE'='-', 'TRUE'='+')))
# plotting with "tell", "me", "why"
qn3 <- with(tstDF, qqnorm2(y, z3))
# plotting with the numeric values
qn4 <- with(tstDF, qqnorm2(y, z4))
##
## test plot, lines, points
##
plot(qn4, type='n') # establish the scales
lines(qn4) # add a line
points(qn4) # add points
##
## Check the objects created above
##
# check qn1
qn1. <- qqnorm(1:3, datax=TRUE, plot.it=FALSE)
qn1.$xlab <- 'y'
qn1.$ylab <- 'Normal scores'
qn1.$z <- tstDF$z1
qn1.$pch <- 1:3
names(qn1.$pch) <- 1:3
qn11 <- qn1.[c(3:4, 1:2, 5:6)]
class(qn11) <- 'qqnorm2'
all.equal(qn1, qn11)
# check qn2
qn2. <- qqnorm(1:3, datax=TRUE, plot.it=FALSE)
qn2.$xlab <- 'y'
qn2.$ylab <- 'Normal scores'
qn2.$z <- tstDF$z2
qn2.$pch <- c('FALSE'=4, 'TRUE'=1)
qn22 <- qn2.[c(3:4, 1:2, 5:6)]
class(qn22) <- 'qqnorm2'
all.equal(qn2, qn22)
# check qn.
qn.. <- qqnorm(1:3, datax=TRUE, plot.it=FALSE)
qn..$xlab <- 'y'
qn..$ylab <- 'Normal scores'
qn..$z <- tstDF$z2
qn..$pch <- c('FALSE'='-', 'TRUE'='+')
qn.2 <- qn..[c(3:4, 1:2, 5:6)]
class(qn.2) <- 'qqnorm2'
all.equal(qn., qn.2)
# check qn3
qn3. <- qqnorm(1:3, datax=TRUE, plot.it=FALSE)
qn3.$xlab <- 'y'
qn3.$ylab <- 'Normal scores'
qn3.$z <- as.character(tstDF$z3)
qn3.$pch <- as.character(tstDF$z3)
names(qn3.$pch) <- qn3.$pch
qn33 <- qn3.[c(3:4, 1:2, 5:6)]
class(qn33) <- 'qqnorm2'
all.equal(qn3, qn33)
# check qn4
qn4. <- qqnorm(1:3, datax=TRUE, plot.it=FALSE)
qn4.$xlab <- 'y'
qn4.$ylab <- 'Normal scores'
qn4.$z <- tstDF$z4
qn44 <- qn4.[c(3:4, 1:2, 5)]
qn44$pch <- NULL
class(qn44) <- 'qqnorm2'
all.equal(qn4, qn44)
##
## Test lines(qn4) without z
##
# just as a test, so this code can be used
# in other contexts
qn4. <- qn4
qn4.$z <- NULL
plot(qn4.)