qqnorm2 {Ecfun} | R Documentation |
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
vector y
or by different data.frame
s
in a list data.
, with different points labeled
according to the different levels of z
.
qqnorm2t
produces a plot with multiple
lines with y
split on different levels of x
,
optionally with different points labeled according to
different levels of z
.
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, ...)
y |
For For |
z |
A variable to indicate different plotting symbols. NOTE: is.logical(z) is replaced by z <- as.character(z). Otherwise, pch[z] would delete symbols in pch for which z is FALSE and would recycle the remaining symbols. That would rarely be what we want. |
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: *** points.qqnorm2 may not work properly for z being integer between 0 and 255. lines.qqnorm2 is more likely to work in such cases. *** No time to fix this as of 2018-01-20. Otherwise, by default, |
... |
Optional arguments. For For |
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 precidence 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\$phc[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\$phc[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, ...)
qqnorm2
returns a list with components, x, y, z, and pch.
Spencer Graves
qqnorm
, qqnorm2s
,
qqnorm2t
plot
points
lines
## ## 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.)