scattersmooth {gamlss.util}R Documentation

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)

Arguments

x the x-variable
y the y-variable
nbin the number of bins required
lambda the smoothing parameter
ndot how many data points to show
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

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.

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

Author(s)

Paul Eilers p.eilers@erasmusmc.nl

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)

[Package gamlss.util version 3.1-0 Index]