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PlackettLuce 0.4.3

  • Update functions to read Preflib Election Data Files (read.soc etc) so that they work for updated Preflib file formats.
  • Update Preflib URLs.

PlackettLuce 0.4.2

CRAN release: 2022-08-15

  • Fix test broken by survival update.

PlackettLuce 0.4.1

CRAN release: 2021-08-16

New features

  • Extend pltree to allow option of modelling log-worth with a linear predictor (via pladmm()).
  • Improved handling of model formula in pladmm(), including possibility to specify contrasts for any factors in the formula.
  • Add anova method for PLADMM models.
  • Add weights argument to pladmm(), allowing aggregated rankings to be modelled, optionally using an aggregate_rankings object to specify rankings and weights together.

Bug fixes

  • Avoid computing variance-covariance matrix in predict.PLADMM(vcov = FALSE) and AIC when new data specified (partial fix to #50).
  • Correct residual df for PLADMM models based on partial rankings (previously assumed all rankings had equal number of items).
  • Update URL for Preflib data sets.

PlackettLuce 0.4.0

CRAN release: 2021-03-29

  • New pladmm function to fit the Plackett-Luce model with log-worth modelled by item covariates.
  • Add three new variables to the beans data. The planting date, and geographical coordinates (@kauedesousa, #41).

PlackettLuce 0.3.2

CRAN release: 2021-01-04

  • Fix test that fails with new behaviour of all.equal().
  • Update citation to use Computational Statistics paper (#44).

PlackettLuce 0.3.1

CRAN release: 2020-10-13

  • Fix Preflib URL.

PlackettLuce 0.3.0

  • Now correctly handles cases where intermediate tie orders are not observed, fixing corresponding tie parameters to zero (#42).

PlackettLuce 0.2-9

CRAN release: 2019-09-16

  • vcov.PlackettLuce() works again for ref = NULL (bug introduced with vcov method in version 0.2-4)
  • avoid dependency on R >= 3.6.0 by providing alternatives to 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.

PlackettLuce 0.2-8

CRAN release: 2019-09-05

PlackettLuce 0.2-7

New Features

  • New "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.
  • New 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.
  • New 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().
  • New 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.
  • New 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.

Changes in behaviour

  • rankings() now sets redundant/inconsistent ranks to NA rather than dropping them. This does not affect the final ranking, unless it is completely NA.
  • The frequencies column in the data frame returned by read.soc() is now named Freq rather than n.
  • The "item" attribute of the data frame returned by read.soc() is now named "items".
  • The labels argument in as.rankings() has been deprecated and replaced by items.
  • grouped_ranking() has been deprecated and replaced by group().
  • The redundant columns in the nascar data have been dropped.

PlackettLuce 0.2-6

CRAN release: 2019-04-01

  • Avoid using isFALSE() for compatibility with R < 3.5.
  • Don’t test number of iterations when comparing models on grouped and ungrouped rankings.

PlackettLuce 0.2-5

CRAN release: 2019-03-20

  • Higher tolerance in tests of vcov() for CRAN Windows test machine.

PlackettLuce 0.2-4

New Features

  • 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).
  • There is now a vcov method for Plackett-Luce trees.

Changes in Behaviour

Bug Fixes

PlackettLuce 0.2-3

CRAN release: 2018-04-09


  • Print methods for "PlackettLuce" and "summary.PlacketLuce" objects now respect options("width").

Changes in Behaviour

  • fitted always returns n which is now weighted count of rankings (previously only returned unweighted count with argument aggregate = TRUE).

Bug fixes

  • Correct vcov for weighted rankings of more than two items.
  • Enable AIC.pltree to work on "pltree" object with one node.

PlackettLuce 0.2-2

CRAN release: 2018-02-19

New features

  • Add AIC.pltree to enable computation of AIC on new observations (e.g. data held out in cross-validation).
  • Add fitted.pltree to return combined fitted probabilities for each choice within each ranking, for each node in a Plackett-Luce tree.

Bug fixes

  • 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
  • PlackettLuce and plfit now work when start argument is set.
  • itempar.PlackettLuce now works with alias = FALSE

PlackettLuce 0.2-1

CRAN release: 2017-12-07

New features

  • Add pkgdown site.
  • Add content to README (fixes #5).
  • Add plot.PlackettLuce method so that plotting works for a saved "PlackettLuce" object


Changes in behaviour

  • maxit defaults to 500 in PlackettLuce.
  • Steffensen acceleration only applied in iterations where it will increase the log-likelihood (still only attempted once iterations have reached a solution that is “close enough” as specified by steffensen argument).

Bug fixes

  • coef.pltree() now respects log = TRUE argument (fixes #19).
  • Fix bug causes lack of convergence with iterative scaling plus pseudo-rankings.
  • [.grouped_rankings] now works for replicated indices.

PlackettLuce 0.2-0

New Features

  • Add vignette.
  • Add data sets pudding, nascar and beans.
  • Add 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.
  • Add 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.
  • Add methods so that rankings and grouped rankings can be added to model frames.
  • Add format methods for rankings and grouped_rankings, for pretty printing.
  • Add [ methods for rankings and grouped_rankings, to create valid rankings from selected rankings and/or items.
  • Add method argument to offer choices of iterative scaling (default), or direct maximisation of the likelihood via BFGS or L-BFGS.
  • Add itempar method for “PlackettLuce” objects to obtain different parameterizations of the worth parameters.
  • Add read.soc function to read Strict Orders - Complete List (.soc) files from

Changes in behaviour

Old behaviour should be reproducible with arguments

npseudo = 0, steffensen = 0, start = c(rep(1/N, N), rep(0.1, D))

where N is number of items and D is maximum order of ties.

  • Implement pseudo-data approach - now used by default.
  • Improve starting values for ability parameters
  • Add Steffensen acceleration to iterative scaling algorithm
  • Dropped ref argument from PlackettLuce; should be specified instead when calling coef, summary, vcov or itempar.
  • qvcalc generic now imported from qvcalc


  • Refactor code to speed up model fitting and computation of fitted values and vcov.
  • Implement ranking weights and starting values in PlackettLuce.
  • Add package tests
  • Add log argument to coef so that worth parameters (probability of coming first in strict ranking of all items) can be obtained easily.

PlackettLuce 0.1-0

  • GitHub-only release of prototype package.