gamlss.util (version 4.3-4)

scattersmooth: Two dimensional Smooth scatter plots

Description

The function produced two dimensional smooth scatter plots. The method used is described in Eilers and Goeman (2004).

Usage

scattersmooth(x, y, nbin = 100, lambda = 1, ndot = 500, csize = 0.3, ticks = TRUE, xlim = c(min(x),  max(x)), ylim = c(min(y), max(y)), show = TRUE,  save = FALSE, data = NULL, xlab = NULL,  ylab = NULL,  cols = heat.colors(10:200),  col.points = "blue", ...)

Arguments

x

the x-variable

y

the y-variable

nbin

the number of bins required for smoothing

lambda

the smoothing parameter

ndot

how many data points to show in the plot

csize

the size of the data points

ticks

whether ticks in the x and y axis appear in the plot

xlim

the x limit

ylim

the y limit

show

whether to show the graph or not

save

whether to save the output as a list or not

data

the data file data

xlab

the x label as character string

ylab

the y label as character string

cols

for changing the color scheme, the defaul is heat.colors(10:200). Other suggestions are gray(0:100/100), heat.colors(101), rainbow(100:200), terrain.colors(101), topo.colors(101), cm.colors(101). Note that if you have the package colorspace in R you can used heat_hcl(100) which was the default before.

col.points

the colours of the points

...

for extra arguments

Value

the function produces a two dimensional smooth plot and saves if save=TRUE a list with the following components:

Hraw

A nbin by nbin matrix containing the bin row data

Hsmooth

A nbib by nbib matrix containing the smooth two dimensional histogram

xgrid

the x-grid

ygrid

the y-grid

xbin

the bin for x values

ybin

the bin for y values

nmiss

number of missing values

seldots

the values of the plotted dots

Details

The function is similar to the function smoothScatter() in graphics but it used penelized bin smoother as described in Eilers and Goeman (2004) rather than kernel smoother.

References

Eilers, P. H. C. and Goeman, J. J. (2004). Enhancing scatterplots with smoothed density. Bioinformatics, Vol 20 no 5, pp 623-628.

Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), Appl. Statist., 54, part 3, pp 507-554.

Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, http://www.jstatsoft.org/v23/i07.

See Also

smoothScatter,gamlss

Examples

m <- 1000
set.seed(pi)
phi <- 2 * pi * runif(m)
rho <- rchisq(m, df = 6)
x <- cos(phi) * rho
y <- sin(phi) * rho
H <- scattersmooth(x, y)
H1 <- scattersmooth(x, y, cols=rainbow(100:200)) 
#  If you have the package colorspace use instead 
# library(colorspace)
# H <- scattersmooth(x, y, cols=heat_hcl(100))
# H1 <- scattersmooth(x, y, cols=rainbow_hcl(100))
data(db)
scattersmooth(age, head,  data=db, cols=terrain.colors(101), ndot=2000, lambda=1)
# or if you have colorspace
#scattersmooth(age, head,  data=db, cols=terrain_hcl(100), ndot=2000, lambda=1)