DISTPLOTS {nsRFA}R Documentation

Distribution plots

Description

Sample values are plotted against their empirical distribution in graphs where points belonging to a particular distribution should lie on a straight line.

Usage

 plotpos (x, ...)
 normplot (x, line=TRUE, ...)
 lognormplot (x, line=TRUE, ...)
 gumbelplot (x, line=TRUE, ...)
 pointspos (x, ...)
 normpoints (x, ...)
 gumbelpoints (x, ...)
 regionalplotpos (x, cod, ...)
 regionalnormplot (x, cod, ...)
 regionallognormplot (x, cod, ...)
 regionalgumbelplot (x, cod, ...)

Arguments

x vector representing a data-sample
line if TRUE (default) a straigth line indicating the normal, lognormal or Gumbel distribution with parameters estimated from x is plotted
cod array that defines the data subdivision among sites
... graphical parameters as xlab, ylab, main, ...

Value

Representation of the values of x vs their empirical probability function F in a cartesian, normal, lognormal or Gumbel plot. F is defined with the plotting position F=(n-0.5)/n. The straigth line (if line=TRUE) indicate the normal, lognormal or Gumbel distribution with parameters estimated from x. The regional plots draw samples of a region on the same plot.
pointspos, normpoints and gumbelpoints are the analogous of points, they can be used to add points or lines to plotpos, normplot, lognormplot and gumbelplot. normpoints can be used either in normplot or lognormplot.

Author(s)

Alberto Viglione, e-mail: alviglio@tiscali.it.

See Also

These functons are analogous to qqnorm; for the distributions, see Normal, Lognormal, LOGNORM, GUMBEL.

Examples

x <- rnorm(30,10,2)
plotpos(x)
normplot(x)
normplot(x,xlab=expression(D[m]),ylab=expression(hat(F)),
         main="Normal plot",cex.main=1,font.main=1)
normplot(x,line=FALSE)

x <- rlnorm(30,log(100),log(10))
normplot(x)
lognormplot(x)

x <- rand.gumb(30,1000,100)
normplot(x)
gumbelplot(x)

x <- rnorm(30,10,2)
y <- rnorm(50,10,3)
z <- c(x,y)
codz <- c(rep(1,30),rep(2,50))
regionalplotpos(z,codz)
regionalnormplot(z,codz,xlab="z")
regionallognormplot(z,codz)
regionalgumbelplot(z,codz)

plotpos(x)
pointspos(y,pch=2,col=2)

x <- rnorm(50,10,2)
F <- seq(0.01,0.99,by=0.01)
qq <- qnorm(F,10,2)
plotpos(x)
pointspos(qq,type="l")

normplot(x,line=FALSE)
normpoints(x,type="l",lty=2,col=3)

lognormplot(x)
normpoints(x,type="l",lty=2,col=3)

gumbelplot(x)
gumbelpoints(x,type="l",lty=2,col=3)

# distributions comparison in probabilistic graphs
x <- rnorm(50,10,2)
F <- seq(0.001,0.999,by=0.001)
loglikelhood <- function(param) {-sum(dgamma(x, shape=param[1], 
                scale=param[2], log=TRUE))}
parameters <- optim(c(1,1),loglikelhood)$par
qq <- qgamma(F,shape=parameters[1],scale=parameters[2])
plotpos(x)
pointspos(qq,type="l")

normplot(x,line=FALSE)
normpoints(qq,type="l")

lognormplot(x,line=FALSE)
normpoints(qq,type="l")


[Package nsRFA version 0.3-1 Index]