pltreeto allow option of modelling log-worth with a linear predictor (via
pladmm(), including possibility to specify contrasts for any factors in the formula.
pladmm(), allowing aggregated rankings to be modelled, optionally using an
aggregate_rankingsobject to specify rankings and weights together.
predict.PLADMM(vcov = FALSE)and
AICwhen new data specified (partial fix to #50).
vcov.PlackettLuce()works again for
ref = NULL(bug introduced with vcov method in version 0.2-4)
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.
input = "orderings"now checks coded values can be matched to item names, if provided.
PlackettLuce()now works with
nspeudo > 0when there are no observed paired comparisons.
?PlackettLucenow gives advice on analysing data with higher order ties.
as.rankings.matrix()introduced in version 0.2-7.
eigsfrom RSpectra vs rARPACK.
"aggregated_rankings"object to store aggregated rankings with the corresponding frequencies. Objects of class
"rankings"can be aggregated via the
as.rankings()will create an
aggregate = TRUE.
as.rankings()also handles pre-aggregated data, accepting frequencies via the
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
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
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.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
na.actionand 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.actionargument for handling of missing rankings.
choices()now return data frames, with list columns as necessary.
rankings()now sets redundant/inconsistent ranks to
NArather than dropping them. This does not affect the final ranking, unless it is completely
read.soc()is now named
"item"attribute of the data frame returned by
read.soc()is now named
as.rankings()has been deprecated and replaced by
grouped_ranking()has been deprecated and replaced by
nascardata 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).
vcovmethod for Plackett-Luce trees.
itempar.PlackettLuce()now always returns a matrix, even for a single node tree.
"summary.PlacketLuce"objects now respect
nwhich is now weighted count of rankings (previously only returned unweighted count with argument
aggregate = TRUE).
AIC.pltreeto enable computation of AIC on new observations (e.g. data held out in cross-validation).
fitted.pltreeto return combined fitted probabilities for each choice within each ranking, for each node in a Plackett-Luce tree.
vcov.PlackettLucenow works for models with non-integer weights (fixes #25).
plot.pltreenow works for
worth = TRUEwith psychotree version 0.15-2 (currently pre-release on https://r-forge.r-project.org/R/?group_id=330)
plfitnow work when
startargument is set.
itempar.PlackettLucenow works with
alias = FALSE
plot.PlackettLucemethod so that plotting works for a saved
maxitdefaults to 500 in
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.edgelistgeneric and method for `“PlackettLuce” objects.
as.data.framemethods so that rankings and grouped rankings can be added to model frames.
formatmethods for rankings and grouped_rankings, for pretty printing.
[methods for rankings and grouped_rankings, to create valid rankings from selected rankings and/or items.
itemparmethod for “PlackettLuce” objects to obtain different parameterizations of the worth parameters.
read.socfunction 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
N is number of items and
D is maximum order of ties.
PlackettLuce; should be specified instead when calling
qvcalcgeneric now imported from qvcalc
coefso that worth parameters (probability of coming first in strict ranking of all items) can be obtained easily.