| flowanalysis | R Documentation | 
Computation of a global selection criterion
for filtering flows values or flow features.
To be use after flowgini and before flowmap.
flowanalysis(tab, fij = NULL, critflow, critlink, result)
| tab | input flow dataset from flowgini | 
| fij | flow value between origin and destination places | 
| critflow | desired level of information significativity. See Details. | 
| critlink | desired level of features density. See Details. | 
| result | resulting filtering criterion value. See Details. | 
-critflow =  desired level of flow's information significativity
(e.g. 80
-critlink = desired level of flow's features density (e.g. 20
of the flow features that represents the more significant information. 
-result="density" returns the desired level of features density as a -result = "significativity" returns the level of flow significativity as a
Bahoken Françoise, 2016,« La cartographie d’une sélection globale de flux, entre ‘significativité’ et ‘densité’ », Netcom Online, 30-3/4 | 2016, Online since 23 March 2017, connection on 05 May 2019. URL : http://journals.openedition.org/netcom/2565 ; DOI : 10.4000/netcom.2565
library(cartograflow)
data(flowdata)
# 1/4: Computes Gini's coefficent
tabgini <- flowgini(ODpts = flows, origin = "i", destination = "j",
                     valflow = "Fij", lorenz.plot = FALSE)
### [1] Gini's coefficent = 73.16 %
# 2/4: Plot Lorenz curve
flowgini(tabgini,
        origin = "i", dest = "j", valflow = "Fij",
        lorenz.plot = TRUE
)
# 3/4: Compute critflow filtering parameter
# critflow = 0.8 #selected criterion
flowanalysis(tabgini, critflow = 0.8, result = "signif")
### [1] "threshold =  11238  ---  flows =  80 % ---  links =  22.94 %"
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