qqnorm2: Normal Probability Plot with Multiple Symbols

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/qqnorm2.R

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'

Usage

1
2
3
4
5
6
7
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 qnorm2, y is a numeric vector for which a normal probability plot is desired.

For plot.qqnorm2, y is ignored; it is included, because the generic plot function requires it.

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 datax argument of qqnorm: If TRUE, the data are displayed on the horizontal rather than the vertical axis. (The default value for datax is the opposite of that for qqnorm.)

x

an object of class qqnorm2.

pch

a named vector of the plotting symbols to be used with names corresponding to the levels of z. If pch is provided, it must either have names corresponding to levels of z, or z must be integers between 1 and length(pch).

Otherwise, if z takes levels FALSE and TRUE (or 0 and 1), pch=c(4, 1) to plot an "x" for FALSE and "o" for TRUE.

Or if z assumes integer values between 0 and 255, by default, the symbols are chosen as described with points.

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, z is coerced to character, and the result is plotted.

...

Optional arguments.

For plot.qqnorm2, they are passed to plot.

For qqnorm2, they are passed to qqnorm and to plot.qqnorm2.

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 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, ...)

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

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
##
## 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.)

Ecfun documentation built on April 6, 2018, 3:10 p.m.