BData: Distributional data containers (BData)

In DistributionalDDA: Distributional Data Analysis in Bayes Spaces

Distributional data containers (BData)

Description

'BData' is the base class for the data containers in DistributionalDDA. A 'BData' object holds a data set of distributions together with the [BayesSpaceBasis] in which they are represented. Several subclasses store the same information in different forms; pick the one that matches how your data arrive, then convert to splines for computation.

Details

# Which representation should I use?

Raw samples

[BDataSamples] – one numeric sample per distribution.

Binned data

[BDataFrequencyHistograms] (counts) or [BDataDensityHistograms] (densities).

Density functions w.r.t. the Lebesgue measure

[BDataPDFs] / [BDataLogPDFs].

Density functions w.r.t. the reference measure

[BDataDensities] / [BDataLogDensities].

Spline coefficients

[BDataSplines] – the compact representation used for computation (PCA, distances, inner products).

# Conversion pipeline The 'as.BData*' converters move between representations. The usual flow is

  Samples / Histograms  ->  Densities  ->  Splines  ->  PDFs 

Converting towards densities/splines requires a basis and is an approximation (the data are projected onto the finite-dimensional spline space); extracting samples or re-expressing a representation as itself is lossless. For most analyses, convert to [BDataSplines] with [as.BDataSplines].

See Also

[BayesSpace], [BayesSpaceBasis], [ReferenceMeasure], [as.BDataSplines], [as.BDataDensities]

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