NEWS.md
pltree
to allow option of modelling log-worth with a linear predictor (via pladmm()
).pladmm()
, including possibility to specify contrasts for any factors in the formula.weights
argument to pladmm()
, allowing aggregated rankings to be modelled, optionally using an aggregate_rankings
object to specify rankings and weights together.predict.PLADMM(vcov = FALSE)
and AIC
when new data specified (partial fix to #50).pladmm
function to fit the Plackett-Luce model with log-worth modelled by item covariates.beans
data. The planting date, and geographical coordinates (@kauedesousa, #41).all.equal()
.vcov.PlackettLuce()
works again for ref = NULL
(bug introduced with vcov method in version 0.2-4)asplit()
read.soi()
and read.toi()
now handle incomplete rankings with very irregular lengths correctly.read.*()
functions for Preflib formats now give a meaningful error when the file or URL does not exist, and a warning if the file is corrupt.as.rankings
with input = "orderings"
now checks coded values can be matched to item names, if provided.PlackettLuce()
now works with nspeudo > 0
when there are no observed paired comparisons.?PlackettLuce
now gives advice on analysing data with higher order ties.as.rankings.matrix()
introduced in version 0.2-7.eigs
from RSpectra vs rARPACK."aggregated_rankings"
object to store aggregated rankings with the corresponding frequencies. Objects of class "rankings"
can be aggregated via the aggregate
method; alternatively rankings()
and as.rankings()
will create an "aggregated_rankings"
object when aggregate = TRUE
. as.rankings()
also handles pre-aggregated data, accepting frequencies via the freq
argument.freq()
function to extract frequencies from aggregated rankings.as.rankings()
can now create a "grouped_rankings"
object, if a grouping index is passed via the index
argument.as.matrix()
methods for rankings and aggregated rankings to extract the underlying matrix of rankings, with frequencies in the final column if relevant. This means rankings can be saved easily with write.table()
.complete()
and decode()
functions to help pre-process orderings before converting to rankings, complete()
infers the item(s) in r’th rank given the items in the other (r - 1) ranks. decode()
converts coded (partial) orderings to orderings of the items in each ordering.read.soi()
, read.toc()
and read.toi()
to read the corresponding PrefLib file formats (for data types “Strict Orders - Incomplete List”, “Orders with Ties - Complete List” and “Orders with Ties - Incomplete List”). An as.aggregated_rankings()
method is provided to convert the data frame of aggregated orderings to an "aggregated_rankings"
object.pltree()
now respects na.action
and will pad predictions and fitted values for na.action = "na.exclude"
if the rankings are missing for a whole group or one of the model covariates has a missing value.PlackettLuce()
now has an na.action
argument for handling of missing rankings.fitted()
and choices()
now return data frames, with list columns as necessary.rankings()
now sets redundant/inconsistent ranks to NA
rather than dropping them. This does not affect the final ranking, unless it is completely NA
.read.soc()
is now named Freq
rather than n
."item"
attribute of the data frame returned by read.soc()
is now named "items"
.labels
argument in as.rankings()
has been deprecated and replaced by items
.grouped_ranking()
has been deprecated and replaced by group()
.nascar
data have been dropped.isFALSE()
for compatibility with R < 3.5.vcov()
for CRAN Windows test machine.PlackettLuce()
now supports MAP estimation with a multivariate normal prior on log-worths and/or a gamma prior on ranker adherence.PlackettLuce()
now returns log-likelihood and degrees of freedom for the null model (where all outcomes, including ties, have equal probability).vcov
method for Plackett-Luce trees.itempar.PlackettLuce()
now always returns a matrix, even for a single node tree.pltree()
or PlackettLuce()
with grouped rankings now work correctly with weights."PlackettLuce"
and "summary.PlacketLuce"
objects now respect options("width")
.AIC.pltree
to enable computation of AIC on new observations (e.g. data held out in cross-validation).fitted.pltree
to return combined fitted probabilities for each choice within each ranking, for each node in a Plackett-Luce tree.vcov.PlackettLuce
now works for models with non-integer weights (fixes #25).plot.pltree
now works for worth = TRUE
with psychotree version 0.15-2 (currently pre-release on https://r-forge.r-project.org/R/?group_id=330)PlackettLuce
and plfit
now work when start
argument is set.itempar.PlackettLuce
now works with alias = FALSE
plot.PlackettLuce
method so that plotting works for a saved "PlackettLuce"
objectbeans
data (which has been updated).?PlackettLuce
and new package?PlackettLuce
. (Fixes #14 and #21).maxit
defaults to 500 in PlackettLuce
.steffensen
argument).coef.pltree()
now respects log = TRUE
argument (fixes #19).[.grouped_rankings]
now works for replicated indices.pudding
, nascar
and beans
.pltree()
function for use with partykit::mob()
. Requires new objects of type "grouped_rankings"
that add a grouping index to a "rankings"
object and store other derived objects used by PlackettLuce
. Methods to print, plot and predict from Plackett-Luce tree are provided.connectivity()
function to check connectivity of a network given adjacency matrix. New adjacency()
function computes adjacency matrix without creating edgelist, so remove as.edgelist
generic and method for `“PlackettLuce” objects.as.data.frame
methods so that rankings and grouped rankings can be added to model frames.format
methods for rankings and grouped_rankings, for pretty printing.[
methods for rankings and grouped_rankings, to create valid rankings from selected rankings and/or items.itempar
method for “PlackettLuce” objects to obtain different parameterizations of the worth parameters.read.soc
function to read Strict Orders - Complete List (.soc) files from https://www.preflib.org.Old behaviour should be reproducible with arguments
= 0, steffensen = 0, start = c(rep(1/N, N), rep(0.1, D)) npseudo
where N
is number of items and D
is maximum order of ties.
ref
argument from PlackettLuce
; should be specified instead when calling coef
, summary
, vcov
or itempar
.qvcalc
generic now imported from qvcalc
PlackettLuce
.log
argument to coef
so that worth parameters (probability of coming first in strict ranking of all items) can be obtained easily.