version 3.19
These functions perform logical operations AND
and OR
, for binary crisp or fuzzy
set membership scores.
fuzzyand(..., na.rm = FALSE)
fuzzyor(..., na.rm = FALSE)
... |
Two or more numerical (calibrated) objects containing membership scores, or a matrix / data frame of calibrated columns. | |||
na.rm |
Logical, indicating whether missing values should be removed. |
A numerical vector of class "QCA_fuzzy"
, with a name
attribute expression.
# ----- # Cebotari & Vink (2013, 2015) # DEMOC*GEOCON*NATPRIDE with(CVF, fuzzyand(DEMOC, GEOCON, NATPRIDE))[1] 0.41 0.06 0.06 0.10 0.10 0.13 0.13 0.13 0.70 0.05 0.54 0.35 0.86 0.75 0.29 0.25 [17] 0.56 0.35 0.49 0.35 0.62 0.38 0.86 0.75 0.88 0.06 0.34 0.12 0.12# same thing with fuzzyand(CVF[, c(1,3,5)])[1] 0.41 0.06 0.06 0.10 0.10 0.13 0.13 0.13 0.70 0.05 0.54 0.35 0.86 0.75 0.29 0.25 [17] 0.56 0.35 0.49 0.35 0.62 0.38 0.86 0.75 0.88 0.06 0.34 0.12 0.12# DEMOC*~GEOCON*NATPRIDE fa <- with(CVF, fuzzyand(DEMOC, 1 - GEOCON, NATPRIDE)) fa[1] 0.05 0.06 0.06 0.10 0.10 0.13 0.13 0.13 0.22 0.83 0.22 0.35 0.05 0.05 0.29 0.05 [17] 0.22 0.56 0.05 0.49 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05attr(fa, "name")[1] "DEMOC*~GEOCON*NATPRIDE"# ETHFRACT + POLDIS with(CVF, fuzzyor(ETHFRACT, POLDIS))[1] 0.88 0.14 0.24 0.37 0.32 0.86 0.86 0.86 0.23 0.95 0.80 0.49 0.06 0.06 0.92 0.59 [17] 0.59 0.69 0.65 0.54 0.83 0.51 0.51 0.58 0.26 0.39 0.39 0.95 0.95# same thing with fuzzyor(CVF[, c(2,4)])[1] 0.88 0.14 0.24 0.37 0.32 0.86 0.86 0.86 0.23 0.95 0.80 0.49 0.06 0.06 0.92 0.59 [17] 0.59 0.69 0.65 0.54 0.83 0.51 0.51 0.58 0.26 0.39 0.39 0.95 0.95fo <- with(CVF, fuzzyor(ETHFRACT, 1 - POLDIS)) fo[1] 0.12 0.95 0.76 0.63 0.95 0.95 0.95 0.95 0.95 0.23 0.54 0.89 0.95 0.95 0.72 0.59 [17] 0.95 0.59 0.54 0.95 0.23 0.95 0.95 0.42 0.95 0.95 0.95 0.95 0.95attr(fo, "name")[1] "ETHFRACT + ~POLDIS"