as.BDataDensities: Converts to a BDataDensities object

In DistributionalDDA: Distributional Data Analysis in Bayes Spaces

Converts to a BDataDensities object

Description

This represents BayesSpace data by a list of density functions, i.e. one density (with respect to the reference measure) per observation. Use this representation to inspect or plot the distributions as densities; for computation (PCA, distances) convert further to splines with [as.BDataSplines].

Usage

as.BDataDensities(x, ...)

## S3 method for class 'BDataDensities'
as.BDataDensities(x, ...)

## S3 method for class 'BDataSplines'
as.BDataDensities(x, ..., basis = getBayesSpaceBasis(x))

## S3 method for class 'BDataLogDensities'
as.BDataDensities(x, ..., basis = getBayesSpaceBasis(x))

## S3 method for class 'BDataPDFs'
as.BDataDensities(x, ..., basis = getBayesSpaceBasis(x))

## S3 method for class 'BDataLogPDFs'
as.BDataDensities(x, ..., basis = getBayesSpaceBasis(x))

## S3 method for class 'BDataHistograms'
as.BDataDensities(
  x,
  ...,
  background = 0,
  basis = getBayesSpaceBasis(x),
  dmu = getPDF(getReferenceMeasure(basis))
)

## S3 method for class 'BDataSamples'
as.BDataDensities(
  x,
  ...,
  method = c("Fisher", "kde"),
  basis = getBayesSpaceBasis(x)
)

Arguments

x	the data to be converted
...	generic arguments potentially used by methods, e.g. to define a method of computation.
basis	the BayesSpaceBasis to be assigned to the object. Necessary if non can be infered from the information presented to the function.
background	the valued for the density outside of the interval.
dmu	the Lebesgue density of the reference measure.
method	a character string defining the method of computation of the density form the data. "Fisher" stands for Fisher scoring and tries to fit an exponential family model given by the subspace of the BayesSpace. It might fail for certain datasets. See [FisherScoringEstimation] for further method parameters. "kde" stands for kernel density estimation. See [kdeDensity] for further possible parameters.

Value

A BDataDensities object (densities w.r.t. the reference measure).

Methods (by class)

• as.BDataDensities(BDataDensities): method for the class itself das nothing

• as.BDataDensities(BDataSplines): constructs the projected functions

• as.BDataDensities(BDataLogDensities): calls [BDataDensities.BDataLogDensities]

• as.BDataDensities(BDataPDFs): divides PDFs by PDF of reference measure

• as.BDataDensities(BDataLogPDFs): divides PDFs by PDF of reference measure

• as.BDataDensities(BDataHistograms): method for histograms (TODO: Uses a very crude heuristic to estimate the log density)

• as.BDataDensities(BDataSamples): constructs a density from the samples

See Also

[.DensityFromHist]

Other BayesSpaceConverters: as.BDataDensityHistograms(), as.BDataFrequencyHistograms(), as.BDataHistograms(), as.BDataLogDensities(), as.BDataLogPDFs(), as.BDataPDFs(), as.BDataSamples(), as.BDataSplines(), idt.BData(), toHistogram()

Examples

X = BDataLogDensities(list(sin,cos),basis=B2Unif01Basis5)
as.BDataDensities(X)

DistributionalDDA documentation built on Oct. 20, 2026, 5:06 p.m.