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plot.MEDseq
:
sortv
options "from.start"
and "from.end"
borrowed from TraMineR
whenseriated
is "observations"
or "both"
for the "clusters"
, "i"
, & "I"
type
plots.type="gating"
when:
x.axis
is supplied via the ...
construct.TraMineR
type
plots when using extra args. via ...
.seriated="none"
is supplied.MoE_entropy
and MoE_AvePP
both gain the arg. group
for computing the average entropiesFALSE
, i.e. old behaviour.TraMineR::seqdef
.matrixStats (>= 1.0.0)
+ related minor speed-ups.CITATION
commands & updated License: GPL (>= 3)
.seqdef
added as an exact copy of TraMineR::seqdef
, to enable experiencedMEDseq
& TraMineR
to use the former without needing to explicitly load the latter.MEDseq_clustnames
gains the arg. weighted=FALSE
for use when size=TRUE
:weighted
arg. to plot.MEDseq
where relevant.dist_freqwH
added for calculating pairwise dissimilarity matrix associated withwKModes(..., freq.weighted=TRUE)
for subsequent use (e.g. silhouettes).plot.MEDseq
function’s type
arg. gains the option "dH"
,2.2-4
or later of the TraMineR
package is installed.plot.MEDseq
also gains the "similarity"
option for its type
argument.MEDseq_AvePP
added.wKModes
now also returns x$tot.withindiff
(i.e. sum(x$withindiff)
).wKModes
when freq.weighted=TRUE
.type="dbsvals"
& type="aswvals"
in plot.MEDseq
.plot.MEDseq
related to its seriated
arg. in G=1
settings.MEDseq_fit
& wKModes
.G>1
.G>1
.MEDseq_meantime
gains the map.size
arg. and a related print
method.summary
(and related print
) methods for MEDCriterion
objects.MEDseq_entropy
added.TraMineR
release, w.r.t. "mt"
and "ms"
plots.WKModes
(& thus related MEDseq_control
init.z
"kmodes"
/"kmodes2"
), by further altering klaR::kmodes
:
wKModes
arg. random
(defaults to TRUE
).modes
is supplied as a number with aggregated data, e.g. "kmodes2"
.MEDseq_fit
& other functions now work for sequence alphabets of any size;dbs
function when supplying clusters
with a noise component.sapply
replaced with vapply
, with other negligible speed-ups.init.z
options "kmodes"
& "kmodes2"
in MEDseq_control
, with new function wKModes
klaR::kmodes
functionklaR
package has been removed from the DESCRIPTION
Suggests:
field).plot.MEDseq
gains the arg. subset
, for use with the TraMineR
type
plots:MEDseq_fit
to crash when weights
are supplied and unique=FALSE
.unique=TRUE
, the default).type="ms"
plots for models with a noise component when SPS=TRUE
.noise.gate
in MEDseq_compare
for G=2
models w/ noise & gating covariates.G
in MEDseq_fit
.plot.MEDseq
gains a number of new arguments:
soft
allows soft cluster membership probabilities to be used for the "d"
, "f"
, "Ht"
, "ms"
,"mt"
type
plots (default: soft=TRUE
) + the "i"
& "I"
plots (default: soft=FALSE
), in aWeightedCluster::fuzzyseqplot()
: previously, all but the "ms"
plot used thesoft=FALSE
, implicitly).sortv
allows overriding the smeth
arg. to instead order observations in certain plotsseriated
is one of "observations"
or "both"
) by the "dbs"
or "asw"
values;WeightedCluster::fuzzyseqplot()
,sortv="membership"
is provided for soft=TRUE
type="I"
plots.weighted
(TRUE
, by default) allows control over whether the weights (if any) are used;"d"
, "f"
, "Ht"
, "i"
, "I"
, "ms"
, & "mt"
type
plots.MEDseq_clustnames
& MEDseq_nameclusts
functions and added SPS
arg. to plot.MEDseq
,MEDseq_meantime
, MEDseq_stderr
, & various/more print
/summary
methods: now certain plots &seriated
options "observations"
& "both"
can now be used for "i"
type plots,"i"
& "I"
type plots for weighted data with seriated observations.predict
, fitted
, & residuals
methods for "MEDgating"
objects, i.e. x$gating
.MEDseq_meantime
gains the arg. wt.size
(defaults to FALSE
).modtype="CU"
.itmax
arg. to MEDseq_control
: the 2nd element of this arg. governs the maximum number of100
to 1000
, which is liable to slownnet::multinom
, but generally reduces the required number of EM iterations.Suggests:
package viridisLite
now only invoked if available.x$gating
object, especially for equalPro
modelsweights
arg. is explicitly supplied to MEDseq_fit
"stslist"
object passed via seqs
has the "weights"
attribute.MEDseq_fit
when the number of states exceeds 9,gating
formulas when there are duplicates.get_MEDseq_results
and how its optional args. are internally handled by plot.MEDseq
.gating
formula which are not found in covars
.type="mean"
option renamed to type="central"
in plot.MEDseq
.type="ms"
plots now work properly when seriated="clusters"
or seriated="both"
."mt"
TraMineR
type
plots.MEDseq_meantime
when MAP=FALSE
.print.MEDseq
for models where DBS &/or ASW statistics weren’t computed."d"
, "f"
, "Ht"
, "i"
, & "I"
plot types now properly account for sampling weights.TraMineR
further, plot.MEDseq
also gains the type
options "ms"
& "mt"
.opti="medoid"
setting.criterion="bic"
is now the default for MEDseq_control
, MEDseq_compare
, andget_MEDseq_results
(previously "dbs"
), with modifications to print
& summary
functions.print.MEDseqtheta
) & plotted (plot.MEDseq(..., type="mean")
) always:preczero
argument has thus been removed from both functions.MEDseq_meantime
gains two new arguments (see documentation for more details):
weighted
(default: TRUE
, old: FALSE
) allows the sampling weights to be used,prop
(default: FALSE
) divides the output when norm=TRUE
by the sequence length.MEDseq_control
gains the arg. random=TRUE
, governing tie-breaking of estimated central sequencerandom=FALSE
.plot.MEDseq
arg. quant.scale=FALSE
replaces old arg. log.scale
: quantiles now usedtype="precision"
.init.z="kmedoids"
initialisation via pam
for unweighted sequences, by using thepamonce
option, based on the cluster
package’s version number.init.z
gains the options "kmodes"
& "kmodes2"
, though only for unweighted sequences:klaR (>= 0.6-13)
package.plot.MEDseq
gains the arg. smeth
, governing the seriation method to be used ("TSP"
, by default).init.z="kmedoids"
is now itself initialised by Ward’s hierarchical clustering.opti
settings (esp. "mode"
).SPS
arg. (default=FALSE
) to print.MEDtheta
& summary.MEDseq
.dbs
gains the optional/experimental arg. clusters
- no change to default.seriated
arg. to plot.MEDseq
:
seriate
to avoid conflict with function seriation::seriate
.seriated
options "clusters"
/"both"
for models with no noise component.seriated="observations"
(the default) now also works for type="I"
plots.seriated="clusters"
now also works for type="dbsvals"
& type="aswvals"
plots.MEDseq_fit
now always internally normalises the weights
to sum to the sample size.noise.gate=FALSE
.noise.gate=FALSE
when G=2
.MEDseq_stderr
now respects the algo
, opti
, & noise.gate
settings of the original model.MEDseq_compare
now returns & prints opti
info where relevant.print
& summary
methods for MEDgating
objects if equalPro=TRUE
.MEDseq_fit
now coerces "character"
covariates to "factor"
.print
method for MEDlambda
objects also.plot.MEDseq(..., type="gating")
.print.MEDseqCompare
gains the args. maxi
& rerank=FALSE
.G=1
models.viridisLite (>= 0.2.0)
to Suggests:
(for plot.MEDseq(..., type="precision")
).matrixStats (>= 0.53.1)
and TraMineR (>= 1.6)
in Imports:
.summary.MEDseq
gains the printing-related argumentsclassification=TRUE
, parameters=FALSE
, and gating=FALSE
.x$params$lambda
now inherits the MEDlambda
class,print
method as per x$params$theta
.x$params$tau
now has informative dimnames
.x.axis
to plot.MEDseq(..., type="gating")
.rmarkdown
to Suggests:
.MEDseq_stderr
is provided for computing the standard errors of theget_MEDseq_results
when what="MAP"
and non-noise models are chosen.summary
on x$gating
.plot.MEDseq
when type="clusters"
for small sample sizes.donttest
examples.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.