covariates_importance-class: Class for covariates importance matrices

Description Usage Arguments Details Value See Also

Description

Objects of this class is the output of the "covariates_importance" object from the bayesPO_fit-class. It can be plotted which uses the graphics package. The print method gives a point-wise estimation, the same seen in the bacplot method. Both plot and boxplot methods use the posterior distribution of the importance.

Usage

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## S3 method for class 'covariates_importance'
print(x, component = "intensity", ...)

## S3 method for class 'covariates_importance'
plot(
  x,
  component = "intensity",
  y = "importance",
  quantiles = c(0.025, 0.5, 0.975),
  ...
)

## S3 method for class 'covariates_importance'
barplot(height, component = "intensity", y, ...)

## S3 method for class 'covariates_importance'
boxplot(x, component = "intensity", ...)

Arguments

x

The covariates_importance object.

component

Either "intensity", "observability" or "both".

...

Other parameters passed to boxplot.

y

Either "interval" or "density". The formal gives vertical credible intervals, and the latter gives separate density plots with the specified quantiles as vertical lines.

quantiles

A 2- or 3-simensional vector with the desired quantiles specified. If 3-dimensiona, the middle point is drawn as a dot when the y parameter is set as "interval".

height

The covariates_importance object.

Details

Objects of this class have two matrices where the Monte Carlo samples on the rows and parameters on the columns. One matrix is for the intensity importance and the other for the observability importance.

Value

The invisible object.

Nothing is returned. Plot is called and drawn on the configured device.

A barplot. See barplot for details. If component is selected as "both", only the second barplot is returned.

A boxplot. See boxplot for details. If component is selected as "both", only the second boxplot is returned.

See Also

barplot.

boxplot.


bayesPO documentation built on Oct. 26, 2021, 5:07 p.m.