diff --git a/DESCRIPTION b/DESCRIPTION index e08a04c..f352fec 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,40 +1,40 @@ Package: PlackettLuce Type: Package Title: Plackett-Luce Models for Rankings -Version: 0.2-4 -Authors@R: c(person("Heather", "Turner", +Version: 0.2-5 +Authors@R: c(person("Heather", "Turner", email = "ht@heatherturner.net", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1256-3375")), person("Ioannis", "Kosmidis", role = "aut", - comment = c(ORCID = "0000-0003-1556-0302")), - person("David", "Firth", role = "aut", - comment = c(ORCID = "0000-0003-0302-2312")), + comment = c(ORCID = "0000-0003-1556-0302")), + person("David", "Firth", role = "aut", + comment = c(ORCID = "0000-0003-0302-2312")), person("Jacob", "van Etten", role = "ctb", comment = c(ORCID = "0000-0001-7554-2558"))) URL: https://hturner.github.io/PlackettLuce/ BugReports: https://github.com/hturner/PlackettLuce/issues Description: Functions to prepare rankings data and fit the Plackett-Luce model - jointly attributed to Plackett (1975) and Luce - (1959, ISBN:0486441369). The standard Plackett-Luce model is generalized - to accommodate ties of any order in the ranking. Partial rankings, in which + jointly attributed to Plackett (1975) and Luce + (1959, ISBN:0486441369). The standard Plackett-Luce model is generalized + to accommodate ties of any order in the ranking. Partial rankings, in which only a subset of items are ranked in each ranking, are also accommodated in - the implementation. Disconnected/weakly connected networks implied by the - rankings may be handled by adding pseudo-rankings with a hypothetical item. - Optionally, a multivariate normal prior may be set on the log-worth - parameters and ranker reliabilities may be incorporated as proposed by - Raman and Joachims (2014) . Maximum a - posteriori estimation is used when priors are set. Methods are provided to - estimate standard errors or quasi-standard errors for inference as well as - to fit Plackett-Luce trees. See the package website or vignette for further + the implementation. Disconnected/weakly connected networks implied by the + rankings may be handled by adding pseudo-rankings with a hypothetical item. + Optionally, a multivariate normal prior may be set on the log-worth + parameters and ranker reliabilities may be incorporated as proposed by + Raman and Joachims (2014) . Maximum a + posteriori estimation is used when priors are set. Methods are provided to + estimate standard errors or quasi-standard errors for inference as well as + to fit Plackett-Luce trees. See the package website or vignette for further details. License: GPL-3 Encoding: UTF-8 LazyData: true Depends: R (>= 2.10) -Imports: Matrix, igraph, methods, partykit, psychotools, +Imports: Matrix, igraph, methods, partykit, psychotools, psychotree, rARPACK, qvcalc, sandwich, stats -Suggests: BiocStyle, BradleyTerry2, BradleyTerryScalable, - Matrix.utils, PLMIX, StatRank, covr, hyper2, kableExtra, knitr, +Suggests: BiocStyle, BradleyTerry2, BradleyTerryScalable, + Matrix.utils, PLMIX, StatRank, covr, hyper2, kableExtra, knitr, lbfgs, gnm, pmr, rmarkdown, testthat, tibble RoxygenNote: 6.1.1 VignetteBuilder: knitr diff --git a/NEWS.md b/NEWS.md index 78f8ffc..ab8916f 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,3 +1,7 @@ +# PlackettLuce 0.2-5 + +* Higher tolerance in tests of `vcov()` for CRAN Windows test machine. + # PlackettLuce 0.2-4 ## New Features diff --git a/cran-comments.md b/cran-comments.md index 044cf34..72eadb9 100644 --- a/cran-comments.md +++ b/cran-comments.md @@ -1,21 +1,16 @@ ## Comments -This update addresses the errors resulting from the change of method for -generating from a discrete uniform distribution. +This is a re-submission to fix the failed tests on r-devel-windows-ix86+x86_64. ## Test environments - -* Local - - Ubuntu 18.04.2 LTS, R 3.5.3 - - Ubuntu 18.04, R Under development (unstable) (2019-03-19 r76252) - - Windows 8, R 3.5.3 -* Via R-hub - - Mac OS 10.11 El Capitan, R-release (experimental) +* Via Win-builder + - Windows Server 2008 (64-bit), R-devel ### Check results -I get one warning and one note on R-hub macOS. +The test environment replicated the error with version 0.2-4. + +This submission (0.2-5), passes with no error/warnings. -* The warning `pandoc: Could not fetch https://www.r-pkg.org/badges/version/PlackettLuce` is due to missing https support in an older version of pandoc. -* The note `Found the following (possibly) invalid URL/DOIs` is a false alarm, I have checked the URLs work and the DOIs resolve (all go to jstor.org). +There remains a note regarding possibly invalid URLs/DOIs which I believe is a false alarm as I have checked these URLs/DOIs. It may be due to a captcha challenge. They are all links to jstor.org. diff --git a/tests/testthat/test-vcov.R b/tests/testthat/test-vcov.R index 496d2ec..40a7ea6 100644 --- a/tests/testthat/test-vcov.R +++ b/tests/testthat/test-vcov.R @@ -94,7 +94,7 @@ test_that("vcov.PlackettLuce approximated by vcov_hessian [gamma prior]", { # should be equal to low tolerance if base on observed Fisher Info though expect_equal(vcov(gamma_prior, type = "observed"), vcov_hessian(gamma_prior), - check.attributes = FALSE, tol = 1e-7) + check.attributes = FALSE, tol = 1e-6) # more data - N.B. this assumes each ranker gives exactly same ranking, # not likely in practice just checking statistical property here # (vcov_hessian slow with large number of adherence par, not practical to @@ -107,7 +107,7 @@ test_that("vcov.PlackettLuce approximated by vcov_hessian [gamma prior]", { check.attributes = FALSE, tol = 1e-3) expect_equal(vcov(gamma_prior, type = "observed"), vcov_hessian(gamma_prior), - check.attributes = FALSE, tol = 1e-7) + check.attributes = FALSE, tol = 1e-6) }) test_that("vcov.PlackettLuce works, grouped rankings [normal + gamma prior]", { @@ -128,7 +128,7 @@ test_that("vcov.PlackettLuce works, grouped rankings [normal + gamma prior]", { # but that based on observed info equals numerical hessian to medium tol expect_equal(vcov(both_priors, type = "observed"), vcov_hessian(both_priors), - check.attributes = FALSE, tol = 1e-7) + check.attributes = FALSE, tol = 1e-6) # gamma prior only (different method for Info inversion) gamma_prior <- PlackettLuce(rankings = G, npseudo = 0, method = "BFGS", gamma = list(shape = 100, rate = 100))