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First public release (prepared for CRAN).
np_quantile_causality()
— a nonparametric
causality-in-quantiles test for first-order lags,
supporting causality in mean and
variance.np_quantile_causality
with fields for statistics, quantiles, bandwidth, type, and sample
size.plot()
method for
np_quantile_causality
objects to visualize test statistics
across quantiles with a reference critical-value line.lrq.causality.test
→
np_quantile_causality
.lrq_causality_test()
calls
np_quantile_causality()
and warns.do.causality.figure()
with the S3 plotting
interface plot.np_quantile_causality()
.gold_oil
(Gold, Oil) for
runnable examples and tests.KernSmooth::dpill()
as a
mean-regression proxy (Yu & Jones, 1998) with quantile-specific
rescaling.lprq2_()
(quantreg-backed).x2
lags were mistakenly
embedded from y2
in the variance case. Now uses
embed(x2, 2)
as intended.inst/CITATION
entries for standard package
citation.gold_oil
.testthat
suite covers:
ggplot
object (skipped on
CRAN).License: MIT + file LICENSE
).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.