Description Usage Arguments Details Value Author(s) See Also Examples
This function plots the prior or posterior set of cumulative distribution functions
represented by a LuckModel
.
It is currently implemented for onedimensional distributions only.
To represent the set of distributions, a pointwise mininum curve and pointwise maximum curve is plotted,
i.e., for each x, min F(x) and max F(x)
are calculated and drawn for a range of x values,
and the area between them can be colored or shaded.
1 2 
object 
An object of a class extending 
xvec 
Either a sequence to plot over or the number of points to plot over,
with default = 100. In the first case, 
epsilon 

control 
A list of controls to address options for appearance of the plot.
Default is the value of 
ylim 
Vector with two elements giving the limit of the plotting region for the ordinate (y axis),
as in usual plots (see, e.g., 
vertdist 
If the cdfs of the distributions corresponding to the four corners of the parameter set
should be plotted. Defaults to 
... 
Further arguments forwarded to 
The minimum and maximum cdf curve drawn by this function are pointwise,
i.e., for each x, min F(x) and max F(x)
over the set of parametric distributions
are calculated and drawn for a range of x values.
The resulting curves usually do not correspond to a single parametric distribution
from the set of distributions, but for certain sets, this may nevertheless be the case.
An example for the former case is the prior plot for a ScaledNormalLuckModel
with both n^(0) and y^(0) intervalvalued;
an example for the latter case is the prior plot for a ScaledNormalLuckModel
where n^(0) is fixed and y^(0) intervalvalued
(see the examples below).
Comparison with the cdfs corresponding to the distributions in the four corners of the parameter set
(drawn with option vertdist = TRUE
) may serve to illustrate this.
The function relies on the function singleCdf
,
which, for an object of a concrete subclass of LuckModel
,
returns values of the cdf for a single distribution of the prior's parametric family.
The function is used for its side effects (the plot).
Gero Walter
luck
for a general description of the package,
singleCdf
for the cdf of a single distribution.
1 2 3 4 5 6  scn1 < ScaledNormalLuckModel(n0=c(2,10), y0=c(3, 4), data=ScaledNormalData(mean=mean(rnorm(5)), n=5))
cdfplot(scn1)
scn2 < ScaledNormalLuckModel(n0=2, y0=c(3, 4))
cdfplot(scn2, xvec=200)
cdfplot(scn1, control=controlList(posterior=TRUE, polygonCol=NA), vertdist=FALSE)
cdfplot(scn1, xvec=seq(2,5,by=0.01))

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