probhat (version 0.4.1)

43_model_plot_methods: Model Plot Methods

Description

Plots methods for models, excluding distribution sets.

Usage

####################################
#discrete kernel smoothing models
#(call plot_dpd)
####################################
# S3 method for dksuv
ph.plotf(sf, data=FALSE, …)
####################################
#continuous kernel smoothing models
#(call plot_cpd, plot_cpd_bv or plot_cpd_tv)
####################################
# S3 method for cksuv
ph.plotf(sf, data=FALSE, …)
# S3 method for cksmv
ph.plotf(sf, in3d=FALSE, data=FALSE, …)
# S3 method for cksc
ph.plotf(sf, …)
# S3 method for cksmvc
ph.plotf(sf, in3d=FALSE, data=FALSE, …)
####################################
#categorical models
#(call plot_dpd)
####################################
# S3 method for catuv
ph.plotf(sf, …)
# S3 method for catc
ph.plotf(sf, …)
####################################
#mixed input
####################################
# S3 method for gmix
ph.plotf(sf, …)
# S3 method for xmix
ph.plotf(sf, …)
####################################
#empirical-like models
#(call plot_cpd)
####################################
# S3 method for eluv
ph.plotf(sf, data=FALSE, …)
####################################
#all continuous univariate models
####################################
# S3 method for cpduv
ph.linesf(sf, …, xlim, n=200)

Arguments

sf

A probability distribution. Refer to the references and see also sections.

in3d

Logical, if true, create a 3D plot. Ignored, if sf has three or more random variables.

data

If true, include a subpanel with data bars/points. Ignored, if x is a quantile function, a conditional distribution, or has three or more random variables

xlim

Length two numeric vector, giving plot range. Currently, ignored for quantile functions.

n

Integer, number of points.

…

Other arguments for plot_dpd, plot_cpd, plot_cpd_bv and plot_cpd_tv.

Details

Refer to the vignette for more information.

Note that these methods call the functions plot_dpd, plot_cpd, plot_cpd_bv and plot_cpd_tv. Please refer to these functions for more information.

References

Refer to the vignette for an overview, references and better examples.

See Also

Succinct Constructors Discrete Kernel Smoothing, Continuous Kernel Smoothing Categorical Distributions, Empirical-Like Distributions

plot_dpd, plot_cpd

plot_cpd_bv, plot_cpd_tv

Examples

# NOT RUN {
prep.ph.data ()

dfh <- pmfuv.dks (traffic.bins, traffic.freq)
cfh <- pdfuv.cks (height)
cfh2 <- pdfmv.cks (trees2 [,-2])

plot (dfh, TRUE)
plot (cfh, TRUE)
plot (cfh2,, TRUE)
# }