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importFrom(utils, tail) to avoid R CMD
check NOTEs.is.symbol() before as.character()
in internal eco atlas extraction to prevent errors on non-symbol
inputs.hrf_bspline() support handling so values for
t > span (and t < 0) are zeroed instead
of wrapping to onset-like values.block_hrf() block integration to include
quadrature step-size scaling, making amplitudes stable across
precision.hrf_sine() and hrf_fourier() to
clamp support to [0, span] and return zero outside the
modeled window.normalise_hrf() to use fixed normalization
constants computed on the HRF support, avoiding data-dependent scaling
across evaluation grids.evaluate.HRF() block-duration summation to use
the same weighted integration scheme as block_hrf().evaluate.Reg(normalize = TRUE) to normalize
regressor outputs consistently across evaluation methods, including
single-trial regressors with different durations.block_hrf(summate = FALSE) to return normalized
block integration (for both single- and multi-basis HRFs) instead of the
legacy pointwise-maximum behavior.hrf_boxcar() function for simple boxcar (step
function) HRFs with optional normalization.hrf_weighted() function for arbitrary
weighted-window HRFs with constant or linear interpolation.regressor() now accepts a list of HRF objects for
trial-varying HRF designs.plot.Reg() method for visualizing regressor
objects.plot_regressors() for comparing multiple regressors
on one plot (ggplot2 or base R).plot_hrfs() for comparing multiple HRF shapes.print.HRF() method for concise HRF summaries.as_hrf() where parameters stored
in the params attribute were never used at evaluation time.
The fix creates a closure that properly captures and applies parameters
during evaluation.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.
Health stats visible at Monitor.