Seriation methods are now reexported from kairos and will be removed in a future release.
RarefactionIndex: S4 class that represent rarefied
species richness.bootstrap(), jackknife() and
simulate() methods to perform bootstrap and jackknife
resampling and to measure diversity in simulated assemblages.heterogeneity(), evenness(),
richness() and composition() methods for
matrix and data.frame.simulate() to simulate observations from a
multinomial distribution.autoplot() and plot() methods for
RarefactionIndex objects.rarefaction() now returns a
RarefactionIndex object.bootstrap_*(), jackknife_*() and
simulate_*().index_heterogeneity(),
index_evenness(), index_richness() and
index_composition().turnover() no longer accept multiple methods as
argument.bootstrap() method for DiversityIndex
objects: resample with replacement instead of simulating observations
from a multinomial distribution.matrix and data.frame.seriate_*() and
permute() now belong to kairos.*_mcd(), *_event(),
*_accumulation(), plot_date() now belong to
kairos.test_fit() and
plot_time() now belong to kairos.DateEvent: S4 class to store the event and
accumulation times of archaeological assemblages.CompositionIndex: S4 class that represent an
asymptotic species richness.IncrementTest: S4 class that represent a Frequency
Increment Test results.eppm() and pvi() to calculate
independence statistics.predict_event() and
predict_accumulation to estimate the event and accumulation
dates of an assemblage.bootstrap_*() and jackknife_*() to
perform bootstrap and jackknife resampling.simulate_evenness() and
simulate_richness() to measure diversity in simulated
assemblages.seriate_average() replaces
seriate_correspondance().seriate_rank() replaces
seriate_reciprocal().seriate_correspondance(),
seriate_reciprocal() and refine_dates(),index_composition() now returns a
CompositionIndex object.similarity() now returns a dist
object.date_mcd() now returns an DateMCD
object.test_fit() now returns an IncrementTest
object.DiversityIndex lost bootstrap() and
jackknife() slots.BootCA to RefineCA.DateModel to DateEvent.RefineCA and DateEvent now inherit from
dimensio::CA.date_mcd(), date_event() and
plot_time() gained a new dates argument.plot_ford() and
plot_bertin().stringsAsFactors = FALSE default).debian-gcc-devel-nold).DiversityIndex, HeterogeneityIndex,
EvennessIndex and RichnessIndex: S4 classes
that represent diversity index.index_heterogeneity() replaces
diversity().index_evenness() replaces evenness().index_richness() replaces richness().index_composition() allows to estimate asymptotic
species richness.plot_diversity() produces a diversity vs
sample size graph and allow to compare estimates with simulated
assemblages.*Matrix classes.diversity(), evenness() and
richness().interactive() is
TRUE and pbapply is installed.Matrix S4 class is now the superclass of all
matrix-like classes.AbundanceMatrix virtual S4 class is defined as the
superclass of CountMatrix, FrequencyMatrix and
IncidenceMatrix.SpaceTime S4 class represents space-time
informations.as_*() coerce a matrix or
data.frame to a CountMatrix,
FrequencyMatrix, IncidenceMatrix,
OccurrenceMatrix or SimilarityMatrix.date_event() replaces dateEvent().date_mcd() allows Mean Ceramic Date estimation.get_dates() and set_dates<- allow to
extract and replace chronological informations in
AbundanceMatrix objects.plot_bertin() and plot_ford() replace
plotBar().plot_date() replaces plotDate().plot_date() gained a method for
AbundanceMatrix objects.plot_heatmap() replaces plotMatrix().plot_rank() replaces plotRank().plot_spot() replaces plotSpot().plot_time() produces an abundance vs. time
graph.refine_dates() and refine_seriation()
replace refine().seriate_reciprocal() and
seriate_correspondance() replace
seriate().test_diversity() allows Shannon diversity test.test_fit() produces a Frequency Increment Test.CountMatrix, FrequencyMatrix and
IncidenceMatrix now also contain the SpaceTime
class.plotBar(), plotMatrix(),
plotRank(), plotSpot(), refine(),
seriate().dateEvent().svd().plot_date() method for DateModel
objects now allows to display an activity or a tempo plot.::
(stop importing the entire package).FactoMinerR::CA() with ca::ca()
(this avoids having to install all {FactoMineR} dependencies when only
one function is used).Matrix object is first created, an identifier
(UUID v4) is generated with generate_uuid(). This ID is
preserved when coercing to another class. This makes it possible to
identify objects representing the same initial data and associate them
with the results of specific computations.get_coordinates() and set_coordinates<-
allow to extract and replace spatial informations in
AbundanceMatrix objects.get_features() allows to convert an
AbundanceMatrix object to a data.frame. It is
intended for compatibility with the sf package.dateEvent() allows to compute
chronological models as described in Bellanger and Husi (2006).DateModel this S4 class stores the results of
dateEvent().SimilarityMatrix this S4 class represents a
(dis)similarity matrix.plotDate() method for DateModel
objects.plotSpot() methods for SimilarityMatrix
and OccurrenceMatrix objects.[ operators for several classes.OccurrenceMatrix now stores the number of times each
pair of taxa occurs together in at least one sample.similarity() now returns an object of class
SimilarityMatrix.plotBar() no longer add confidence interval by
default.similarity() gained a new estimator: binomial
co-occurrence assessment method (similarity between types).seriate() gained a new argument to pass a
BootCA object.similarity() now returns a symmetric matrix.richness() gained new estimators:Description field of the
DESCRIPTION file.BootCA this S4 class stores partial bootstrap CA-based
seriation results.[[ operators acting on PermutationOrder
and BootCA to extract parts.refine() method for CountMatrix now use
stats::rmultinorm() for partial bootstrap CA.similarity() gained a new estimator: the
Brainerd-Robinson coefficient of similarity.