Imports: cli (>= 2.3.0), fansi, glue, lifecycle, rlang (>= 1.0.2), utf8

Authors@R: c(person("Joris","Meys", email = "Joris.Meys@UGent.be", role = c('aut', 'cre')),person("Jan","De Neve", email = "Jan.DeNeve@UGent.be", role = 'aut'), person("Nick","Sabbe", role = 'aut'))
Author: Joris Meys [aut, cre], Jan De Neve [aut], Nick Sabbe [aut]
Description: Fit a probabilistic index model as described in
modeling function has changed in this new version. The old version is
still available at R-Forge. You can install the old package
using install.packages('pimold', repos = 'http://R-Forge.R-project.org').
Collate: 'CreateScoreFun.R' 'DysData.R' 'EngelData.R' 'Estimators.R'
'InternalObjects.R' 'LR.R' 'MHData.R' 'P.R' 'SUData.R'
'penv.R' 'pim.R' 'pim.fit.R' 'pimdata.R' 'poset.R' 'print.R'

Authors@R: c(person("Joris","Meys", email = "Joris.Meys@UGent.be", role = c('aut', 'cre')),
person("Jan","De Neve", email = "Jan.DeNeve@UGent.be", role = 'aut'),
person("Gustavo", "Guimaraes de Castro Amorim", role = 'aut'))
Author: Joris Meys [aut, cre], Jan De Neve [aut], Nick Sabbe [aut], Gustavo Guimaraes de Castro Amorim [aut]

Gustavo Guimaraes de Castro Amorim [aut]
Imports: methods, utils, stats4, nleqslv, BB

Title: Prediction Intervals for Random-Effects Meta-Analysis
person("Kengo", "Nagashima", email = "nshi1201@gmail.com",
person("Hisashi", "Noma", role = c("aut")),
person("Toshi A.", "Furukawa", role = c("aut")))
Description: An implementation of prediction intervals for random-effects meta-analysis:
Packaged: 2018-04-06 14:21:04 UTC; NAGASHIMA

Packaged: 2018-05-10 18:40:58 UTC; NAGASHIMA

Packaged: 2018-09-14 08:53:52 UTC; NAGASHIMA

Packaged: 2018-09-14 17:57:02 UTC; NAGASHIMA

Imports: stats, Rcpp (>= 0.12.18), ggplot2 (>= 3.0.0), utils
Packaged: 2019-03-11 07:32:30 UTC; Nagashima

Title: Fast and Stable Estimation of the Probability of Informed
Authors@R: person("Andreas", "Recktenwald", email = "a.recktenwald@mx.uni-saarland.de",
Description: Utilities for fast and stable estimation of the probability of
informed trading (PIN) in the model introduced by Easley et al. (2002)
<DOI:10.1111/1540-6261.00493> are implemented. Since the basic model developed
former due to equating the intensity of uninformed buys and sells, functionalities
can also be applied to this simpler model structure, if needed.
Imports: stats, fastcluster, lubridate, ggplot2, reshape2, scales