plotnonp {BayesX}R Documentation

Plotting Nonparametric Function Estimates


Plots nonparametric function estimates obtained from BayesX


plotnonp(data, x = 2, y = c(3, 4, 5, 7, 8), ylim = NULL, 
         lty = c(1, 2, 3, 2, 3), cols = rep(1, length(y)), month, year, step=12, 
         xlab, ylab, ...)



Either the name of a file or a data frame containing the estimation results.


Defines the x-axis in the plot. Either the name of a variable in data or the index of the corresponding column.


Defines the variables to be plotted against x. May be either a vector of names of variables in data or the corresponding indices. The default choice corresponds to the point estimate plus two confidence bands.


Since plotnonp plots multiple y-variables, it automatically determines the appropriate ylim to make all curves visible. Argument ylim allows to override this default behaviour with fixed values.


Vector of line types used for plotting (must have the same length as y). The default corresponds to solid lines for the point estimate and dashed and dotted lines for the confidence bands.


Vector of colors used for plotting (must have the same length as y). Default are black lines.

month, year, step

Provide specific annotation for plotting estimation results for temporal variables. month and year define the minimum time point whereas step specifies the type of temporal data with step=4, step=2 and step=1 corresponding to quartely, half yearly and yearly data.

xlab, ylab

plotnonp constructs default labels that can be overwritten by these arguments


Further arguments to be passed to the interval call of plot such as type, etc.


Felix Heinzl, Andreas Brezger and Thomas Kneib

See Also



res <- read.table(system.file("examples/nonparametric_f_x_pspline.res", 
                              package="BayesX"), header=TRUE)
plotnonp(res, x="x")
plotnonp(res, x="x", y="pmean")
plotnonp(res, x="x", y="pmed")
plotnonp(res, x="x", y="pmed", ylim=c(-2,2))
plotnonp(res, x="x", y=c("pmean", "pqu10", "pqu90"), lty=c(1,1,1), 
plotnonp(res, xlab="some variable", ylab="f(some variable)", 
         main="Nonlinear effect of some variable", sub="penalised spline")

res <- read.table(system.file("examples/nonparametric2_f_time_pspline.res", 
                              package="BayesX"), header=TRUE)
plotnonp(res, month=1, year=1980, step=12)

res <- res[1:18,]                                           
plotnonp(res, month=1, year=1980, step=12)

[Package BayesX version 0.3-1 Index]