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hodges_ajne_test(),
rao_spacing_test(), watson_williams_test(),
uniform_scores_test(), equal_kappa_test(), and
walraff_test(),weighted_rayleigh_perm() now returns an
"htest" object, like
rayleigh_test_perm().weighted_rayleigh() with mu = NULL now
performs a weighted Rayleigh test instead of a V-test around the
estimated mean direction, and gains an alpha argument.watson_test(dist = "vonmises") no longer returns a
p-value, because only tabulated critical values are available. The
p-value range is shown in the printed output and returned as
p.range.U2 for
watson_two_test_perm() (was G) and
R* for watson_wheeler_test_perm() (was
G). rayleigh_test_perm() now labels the mean
resultant length Rbar (was R).weighted_rayleigh() used the sample size instead of the
effective sample size for unequal weights, which made the test
anti-conservative. Its decision message compared the statistic with the
p-value.weighted_rayleigh_perm() simulated the null
distribution without the weights, so it rejected almost always when
mu = NULL.watson_test(dist = "uniform") ignored
axial = TRUE.watson_two_test() and
watson_two_test_perm() are now corrected for ties,
e.g. azimuths rounded to whole degrees. Identical samples previously
gave a non-zero U².watson_two_test_perm() and
watson_wheeler_test_perm() did not wrap doubled axial
angles because of operator precedence.watson_test() no longer fails with
alpha = NULL.ar_test(), watson_two_test_perm(),
watson_wheeler_test_perm(),
rayleigh_test_perm(), weighted_rayleigh_perm()
and rao_spacing_test() are vectorised and run their
simulations in chunks to limit memory use.kuiper_test() now returns alpha and
reject, as documented.watson_two_test() warns for combined sample sizes below
18.watson_wheeler_test_perm() gives tied values their
average rank, so its result is reproducible.rayleigh_test_perm() and
weighted_rayleigh_perm() are described as Monte Carlo tests
rather than permutation tests.watson_wheeler_test_perm() is described as a test of
equal distributions, not equal means.ar_test()), Watson-Wheeler permutation test
(waton_wheeler_test_perm()), Watson 2-sample permutation
test watson_two_test_perm(), and permutation Rayleigh test
(rayleigh_test_perm().fillhoming and
striae) added for testing directional datastress2grid(), rayleigh_test(),
kuiper_test() and watson_test()circular_plot() (and thus in
rose()) now a placed text instead of
mtext.ortensor2d() to calculate summary statistics for
axial datadata2PoR(): Convenience function to add PoR
coordinates and PoR azimuths to datageom_azimuth() and
geom_azimuthpoint(): convenience functions to plot
directions as bars in ggplot2weighting() convenience function to assign
weightings for angles based on optional algorithmsest.kappa() now uses approximation (as precise as
original but faster). Original algorithm now in
est.kappa.MLE()relative_rotation()isTRUE or
isFALSEdownload_WSM() has option "version" for
the user to decide which WSM version should be downloaded. The most
recent 2025 version is the default.parse_quality() assigns an uncertainty of 90 degrees to
X-ranked stress data in the 2025 WSM version.est.kappa(): converts to directional
data by doubling the anglescircular_summary() now
optional due to performance issuesstress2grid() have been
renamed to me more alike with {gstat}circular_summary()stress2grid() and friendsdistance_binned_stats() to calculate
summary statistics along distance intervals: The function supersedes
distroll_circstats() and friends because it is faster and
more flexiblePoR_to_geographical() and
geographical_to_PoR() now accept data.frame,
sf or raster as inputPoR_azimuth() function to transform directions in
the PoR coordinate system / doesn’t need to be Shmax datacircular_distance() and
circular_dispersion() when using
axial=FALSEdvm() when using
axial=FALSEcpm_modelsdvm(), pvm(),
qvm() and rvm()PoR_distance(): function to calculate distance to
PoRload_wsm()rose() diagramsuperimposed_shmax() and
superimposed_shmax_PB() to model the stress orientation
using multiple plate boundariesdownload_WSM2016()weighted_rayleigh()spatstat.geom to
spatstat.univarstress2grid()deviation_norm() accepts two argumentsdispersion_grid() deprecated and replaced by
kernel_dispersion() (details in vignette E)rose() (e.g. symmetrical fans when axial
data is plotted)rose()rose()est.kapp()watson_test()rose() diagramrayleigh_test()prd_err()rose() diagramsquick_plot()sp class output for small circles, great circles and
loxodromes deprecatedcircular_mean(), circular_median()euler_loxodrome() function to construct loxodromes
directing towards an given point or Euler pole.NEWS.md file to track changes to the
package.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.