Description Usage Arguments Details Value Author(s) References Examples

`surCoin`

produces a network object of coincidences from a data frame converting variables into dichotomies.

1 2 3 4 5 6 7 8 9 | ```
surCoin(data,variables=names(data), commonlabel=NULL,
dichotomies=NULL, valueDicho=1, metric=NULL, exogenous=NULL,
weight=NULL, subsample=FALSE, pairwise=FALSE,
minimum=1, maximum=nrow(data), sort=FALSE, decreasing=TRUE,
frequency=FALSE, percentages=TRUE,
procedures="Haberman", criteria="Z", Bonferroni=FALSE,
support=-Inf, minL=-Inf, maxL=Inf,
directed=FALSE, diagonal=FALSE, sortL=NULL, decreasingL=TRUE,
igraph=FALSE, coin=FALSE, dir=NULL, ...)
``` |

`data` |
a data frame. |

`variables` |
a vector of variables included in the previous data frame. |

`commonlabel` |
a vector of variables whose names are to be included in nodes labels. |

`dichotomies` |
a vector of dichotomous variables to appear as just one category. |

`valueDicho` |
value or list of values (not vector) to be selected for dichotomous variables. Default is 1. |

`metric` |
a vector of metrics. |

`exogenous` |
a vector of variables whose relations amongst them are of no interest. None by default. |

`weight` |
a vector of weights. Optimal for data.framed tables. |

`subsample` |
retrict the analysis to scenarios with at least one event. |

`pairwise` |
Pairwise mode of handling missing values if TRUE. Listwise by default. |

`minimum` |
minimum frequency to be considered. |

`maximum` |
maximum frequency to be considered. |

`sort` |
sort the coincidence matrix according to frequency of events. |

`decreasing` |
decreasing or increasing sort of the matrix. |

`frequency` |
a logical value true if frequencies are to be shown. Default=FALSE. |

`percentages` |
a logical value true if percentages are to be shown. Default=TRUE. |

`procedures` |
a vector of statistics of similarity. See below. |

`criteria` |
statistic to be use for selection criteria. |

`Bonferroni` |
Bonferroni criterium of the signification test. |

`support` |
minimum value of the frequency of the coincidence to be edged. |

`minL` |
minimum value of the statistic to include the edge in the list. |

`maxL` |
maximum value of the statistic to include the edge in the list. By default is +Inf, except if criteria="Z" or criteria="hyp", in which case it is .5. It is recommnended to change it to .05 if data has been sampled. |

`directed` |
includes same edges only once. |

`diagonal` |
includes auto-links. |

`sortL` |
sort the list according to the values of a statistic. See below. |

`decreasingL` |
order in a decreasing way. |

`igraph` |
Produces an igraph object instead of a netCoin object if TRUE. |

`coin` |
Only return the coincidences matrix if TRUE. |

`dir` |
a "character" string representing the directory where the web files will be saved. |

`...` |
Any netCoin argument. |

Possible measures in procedures are

Frequencies (f), Relative frequencies (x), Conditional frequencies (i), Coincidence degree (cc), Probable degree (cp),

Expected (e), Confidence interval (con)

Matching (m), Rogers & Tanimoto (t), Gower (g), Sneath (s), Anderberg (and),

Jaccard (j), Dice (d), antiDice (a), Ochiai (o), Kulczynski (k),

Hamann (ham), Yule (y), Pearson (p), odds ratio (od), Rusell (r),

Haberman (h), Z value of Haberman (z),

Hypergeometric p greater value (hyp).

Convert a matrix into an edge list (shape).

This function creates a netCoin object (or igraph) and, if stated, a folder in the computer with an HTML document named index.html which contains the produced graph. This file can be directly opened with your browser and sent to a web server to work properly.

Modesto Escobar, Department of Sociology and Communication, University of Salamanca. See https://sociocav.usal.es/blog/modesto-escobar/

Escobar, M. and Martinez-Uribe, L. (2020)
Network Coincidence Analysis: The `netCoin`

`R`

Package.
*Journal of Statistical Software*, **93**, 1-32.
doi: 10.18637/jss.v093.i11.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
# A data frame with two variables Gender and Opinion
frame <- data.frame(Gender=c(rep("Man",3),rep("Woman",3)),
Opinion=c("Yes","Yes","No","No","No","Yes"))
surCoin(frame,commonlabel="") # network object
# A data frame with two variables (Gender and Hand) and nodes
input <- data.frame(
Gender = c("Women", "Men", "Men", "Women", "Women","Men",
"Men", "Men", "Women", "Women", "Men", "Women"),
Hand = c("Right", "Left","Right", "Right", "Right", "Right",
"Left", "Right", "Right", "Left","Right", "Right"))
nodes <- data.frame(
name = c("Gender:Men","Gender:Women", "Hand:Left", "Hand:Right"),
label = c("Women(50\u25)","Men(50\u25)",
"Left hand(25\u25)", "Right hand(75\u25)"))
G <- surCoin(input, nodes=nodes, proc=c("h","i"), label="label",
ltext="i", showArrows=TRUE, maxL=.99)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.