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probhat (version 0.3.1)

35_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
plot(x, data=FALSE, …, freq)

#################################### #continuous kernel smoothing models #(call plot_cpd, plot_cpd_bv or plot_cpd_tv) #################################### # S3 method for cksuv plot(x, data=FALSE, …) # S3 method for cksmv plot(x, in3d=FALSE, data=FALSE, …) # S3 method for cksc plot(x, …) # S3 method for cksmvc plot(x, in3d=FALSE, data=FALSE, …)

#################################### #categorical models #(call plot_dpd) #################################### # S3 method for catuv plot(x, …, combine, freq, space)

#################################### #empirical-like models #(call plot_cpd) #################################### # S3 method for eluv plot(x, data=FALSE, …)

#################################### #all continuous univariate models #################################### # S3 method for cpduv lines(x, …)

Arguments

x

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

combine

Logical, if true, combine the bars. By default, categorical distributions are separate and others are combined.

freq

Logical, if true, return frequencies rather than probabilities. Refer to the value section. Default depends on the object. Refer to the corresponding constructors.

space

Numeric, the space (in mm) between bars. Ignored, unless combine is false.

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

Run this code
# NOT RUN {
ph.data.prep ()

dfh <- pmfuv.dks (traffic.bins, traffic.freq, lower=0)
cfh <- pdfuv.cks (height)

cfh2 <- pdfmv.cks (trees [,-2])
cfh3 <- pdfmv.cks (trees)

plot (dfh, TRUE)
plot (cfh, TRUE)
plot (cfh2,, TRUE)
plot (cfh3)
# }

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