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ffpo() and ffpo_2d() for
defining partially observed functional terms in model formulae,
po_fit() and po_2d_fit() for fitting the
corresponding regression models, and the data generators
data_generator_po_1d() and
data_generator_po_2d().po_fit() and po_2d_fit() now return the
estimated functional coefficient together with its pointwise confidence
intervals.mfpca_vd(), a multivariate functional principal
component analysis for variable domain data, together with a
plot() method for the estimated eigenfunctions and
scores.plot_ci() where the input object was
referenced through the wrong variable, causing the function to error
before producing a plot.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.