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as.BDataDensities() and
as.BDataLogDensities() on histogram objects applied the bin
weights in reversed order, so that all histogram-derived step densities
(and everything computed from them) were mirrored in the domain
(.DensityFromHist()/.LogDensityFromHist()).
Quantities that are invariant under a coherent relabeling of the domain
(variances, distances, depths, explained-variance shares) were only
mildly affected through the unequal bin widths, but plotted densities,
means, and eigenfunctions appeared reflected. Densities supplied as
functions (BDataPDFs, BDataDensities) were not
affected.ReferenceMeasureUniform() gains a seed
argument: the Monte Carlo sample of the reference measure is drawn under
that seed and the global RNG state is restored afterwards (same
convention as simulate()). Reproducibility of a reference
measure no longer depends on the global seed being set immediately
before construction.plot() on princomp.BData objects with
type = "scores" now accepts pch (recycled
across observations), so groups can be distinguished by plotting symbol
in addition to color.plot() on multivariate SFPCA objects
(type = "eigenfunctions") forwards ... to the
panel set-up call, so axis labels such as xlab and
ylab can be customized.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.