Title: Structural Handling of Finnish Personal Identity Numbers
person("Pyry", "Kantanen", email = "pyry.kantanen@gmail.com", role = c("aut", "cre")),
person("Mans", "Magnusson", role = "aut"),
person("Jussi", "Paananen", role = "aut"),
Description: Structural handling of Finnish identity numbers (persons and companies); extract information, check ID validity and diagnostics.
Suggests: Cairo, checkmate, lubridate, dplyr, knitr, testthat,
Packaged: 2020-10-16 07:51:07 UTC; pyrykantanen

Title: Structural Handling of Finnish Personal Identity Codes
Description: Structural handling of Finnish identity codes (natural persons and
organizations); extract information, check ID validity and diagnostics.
Suggests: Cairo, knitr, testthat, rmarkdown, covr, dplyr
Packaged: 2022-05-20 12:37:03 UTC; pyrykantanen
Author: Pyry Kantanen [aut, cre] (<https://orcid.org/0000-0003-2853-2765>),

Title: Heuristics Including Take the Best and Unit-Weight Linear
person("Jean", "Whitmore", email = "jeanimal@gmail.com",
person("Daniel", "Barkoczi", email = "barkoczi@mpib-berlin.mpg.de",
Description: Implements various heuristics like Take The Best and
unit-weight linear, which do two-alternative choice: which of
two objects will have a higher criterion?  Also offers functions
to assess performance, e.g. percent correct across all row pairs
in a data set and finding row pairs where models disagree.
New models can be added by implementing a fit and predict function--
Suggests: devtools, ggplot2, glmnet, knitr, plyr, reshape, reshape2,
Packaged: 2016-06-18 03:03:57 UTC; jeanwhitmore

Packaged: 2016-07-17 17:26:08 UTC; jeanwhitmore

person("Daniel", "Barkoczi", email = "dnlbrkc@gmail.com",
Packaged: 2019-08-19 14:36:33 UTC; jeanwhitmore

see vignette.  Take The Best was first described in: Gigerenzer, G.
of these heuristics were run on many data sets and analyzed in:
Gigerenzer, G., Todd, P. M., & the ABC Group (1999).
Packaged: 2021-09-07 02:59:06 UTC; jeanwhitmore

Title: Discovery of Process Models with the Heuristics Miner
Description: Provides the heuristics miner algorithm for process discovery
as proposed by Weijters et al. (2011) <doi:10.1109/CIDM.2011.5949453>. The
algorithm builds a causal net from an event log created with the 'bupaR'
package. Event logs are a set of ordered sequences of events for which
'bupaR' provides the S3 class eventlog(). The discovered causal nets
can be visualised as 'htmlwidgets' and it is possible to annotate them with
the occurrence frequency or processing and waiting time of process
Imports: DiagrammeR (>= 1.0.0), magrittr, dplyr, processmapR (>=
0.3.1), petrinetR, bupaR, purrr, tidyr, rlang, scales, Rcpp,
Suggests: eventdataR, edeaR, svgPanZoom, DiagrammeRsvg