PCC.Exploratory: PCC Exploratory methods
In stemmatology: Stemmatological Analysis of Textual Traditions

Description Usage Arguments Details Value Author(s) References See Also Examples

This is the global function for exploratory methods of the PCC family. It interactively makes use of the lower-level exploratory functions, to assess conflicts between variant locations, eliminate problematic configurations or identify likely contaminations.

1 2	PCC.Exploratory(x, omissionsAsReadings = FALSE, alternateReadings = FALSE, pauseAtPlot = FALSE, ask = TRUE, threshold = NULL, verbose = FALSE)

`x`	if `alternateReadings = FALSE` (default), a numeric matrix, with witnesses in columns, variant locations in rows, and readings coded by a number; if `alternateReadings = TRUE`, a character matrix, with witnesses in columns, variant locations in rows, and, in each cell, one or several readings, coded by numbers and separated by a comma (e.g. '1,2,3', if the witness has three different readings).
`omissionsAsReadings`	logical; if `TRUE`, omissions are treated as variant readings (and taken into account in determining conflicts between variant locations or in computing severe disagreements between witnesses). Default: `FALSE`.
`alternateReadings`	logical; if `TRUE`, a witness can have multiple variants for a single variant location (contaminated manuscripts, editio variorum, …), encoded as comma-separated values. Default: `FALSE`.
`pauseAtPlot`	logical; if `TRUE`, the algorithms stops at each plot during the execution of `PCC.contam` (by setting graphical parameter `ask = TRUE`). Default: `FALSE`.
`ask`	logical; if `FALSE`, decisions will be made without asking the user for input. Default: `TRUE`
`threshold`	numeric; the centrality threshold above which variant locations are considered to be over-conflicting. Used only with `ask = FALSE`.
`verbose`	logical; if `FALSE`, the function will only return the results, without information on the operations. Default: `FALSE`.

This function is meant to guide the user through the process of assessing and eliminating unreliable variant locations and/or identify competing genealogies (i.e. contamination), as described in Camps & Cafiero 2015.

It starts by computing and plotting the network of conflicting variant locations (i.e. variant locations that present contradictory genealogical information), by calling PCC.conflicts, and then interactively aids the user in determining overconflicting variant locations (with PCC.overconflicting), eliminating problematic variant locations (PCC.elimination), detecting contamination (PCC.contam) or creating new databases reflecting competing genealogies (PCC.equipollent).

According to the choices made by the user, the output can be an object belonging to one of the following classes: pccConflicts, pccOverconflicting, pccContam or pccEquipollent.

Jean-Baptiste Camps (jbcamps@hotmail.com) & Florian Cafiero

Camps, Jean-Baptiste, and Florian Cafiero. ‘Stemmatology: An R Package for the Computer-Assisted Analysis of Textual Traditions’. Proceedings of the Second Workshop on Corpus-Based Research in the Humanities (CRH-2), edited by Andrew U. Frank et al., 2018, pp. 65–74, https://halshs.archives-ouvertes.fr/hal-01695903v1.

Camps, Jean-Baptiste, and Florian Cafiero. ‘Genealogical Variant Locations and Simplified Stemma: A Test Case’. Analysis of Ancient and Medieval Texts and Manuscripts: Digital Approaches, edited by Tara Andrews and Caroline Macé, Brepols, 2015, pp. 69–93, https://halshs.archives-ouvertes.fr/halshs-01435633, DOI: 10.1484/M.LECTIO-EB.5.102565.

Poole, Eric. ‘L’analyse stemmatique des textes documentaires’. La pratique des ordinateurs dans la critique des textes, Paris, 1979, p. 151-161.

Poole, Eric, ‘The Computer in Determining Stemmatic Relationships’. Computers and the Humanities, 8-4 (1974), p. 207-16.

PCC.conflicts, PCC.overconflicting, PCC.elimination, PCC.contam, PCC.equipollent.

# Load data
data(fournival)
## Not run: 
# Interactive mode
# or alternatively, import it
#fournival = import.TEIApparatus(file = "myFournival.xml", 
#                      appTypes = c("substantive"))
# Analyse it with the PCC functions
PCC.Exploratory(fournival)

## End(Not run)

# Non interactive mode
PCC.Exploratory(fournival, ask = FALSE, threshold = 0.06)