| Title: | Helper Functions for QCA in R |
| Version: | 0.2.3 |
| Author: | Jirka Lewandowski <jirka.lewandowski@wzb.eu> [aut, cre] |
| Maintainer: | Jirka Lewandowski <jirka.lewandowski@wzb.eu> |
| Description: | Helper functions for Qualitative Comparative Analysis: evaluate and plot Boolean formulae on fuzzy set score data, apply Boolean operations, compute consistency and coverage measures. |
| Depends: | R (≥ 3.1.0) |
| Imports: | stringr (≥ 0.6.2), ggplot2 (≥ 0.9.3.1), directlabels (≥ 2013.6.15), graphics, QCA (≥ 2.5) |
| License: | GPL (≥ 3) |
| LazyData: | true |
| RoxygenNote: | 5.0.1 |
| NeedsCompilation: | no |
| Packaged: | 2017-01-03 20:44:37 UTC; jlewando |
| Repository: | CRAN |
| Date/Publication: | 2017-01-03 23:54:33 |
QCAtools.
Description
Several convenience functions for QCA in R
And
Description
Logical 'and' of two conditions
Logical 'or' of two conditions
Logical 'not' of a condition
Usage
and(v1, v2)
or(v1, v2)
not(v)
Arguments
v1 |
A vector of fuzzy set scores of cases |
v2 |
A vector of fuzzy set scores of cases |
v |
A vector of fuzzy set scores of cases |
Value
the fuzzy set scores of the logical conjunction of v1 and v2 for each case, i.e. the minimum in each component
the fuzzy set scores of the logical disjunction of v1 and v2 for each case, i.e. the maximum in each component
the fuzzy set scores of the negation of v for each case, i.e. 1-v
Examples
and(c(0,0.5,1), c(0.25, 0.75, 0.75))
or(c(0,0.5,1), c(0.25, 0.75, 0.75))
not(c(0,0.5,1))
Compute the consistency value
Description
Computes the consistency score of "formula1 -> formula2" (sufficient condition)
or "formula1 <- formula2" (necessary condition), depending on whether type
is "->" or "<-".
If type is "<->" it computes an equivalence score of formula1 and formula2
via the formula sum(min(X,Y))/(sum(max(X,Y))
Usage
consistency(formula1, type = "->", formula2, data)
Arguments
formula1 |
A string, list of strings or function representing a Boolean formula in disjunctive normal form |
type |
either "->", "<-" or "<->", depending on the direction of the implication that is to be evaluated |
formula2 |
A string, list of strings or function representing a Boolean formula in disjunctive normal form |
data |
A data frame where the rows represent cases and the columns the sets. Column names must be as in the formula. |
Details
Compute a consistency score for an implication/necessity/sufficiency statement.
If formula is a function, it must take a data.frame and return
a vector.
If formula is a string or list of strings, the following conventions hold:
Set names must be capitalized in the formula and the data; if they are
lowercase, they are interpreted as the negation of the set.
If formula is a string, logical 'or' is expressed as a '+',
and logical 'and' as a '*'.
If formula is a list of strings, the strings are assumed to be
the dosjuncts and are concatenated with '+'.
The formula must be in disjunctive normal form, i.e. it must be a disjunction of
conjunctions of elementary or negated elementary sets. Example:
A*b*C + a*B
Value
the consistency score of the implication described by formula1, type and formula2
Examples
require(QCA)
data(d.urban)
consistency("MLC + FRB", "->", "CP", d.urban)
Evaluate a formula
Description
When given a Boolean formula (see details) and a data.frame of cases and fuzzy
set score for conditions, computes for each case the score of the membership
in the set described by the formula
Usage
evaluate_dnf(data, formula)
Arguments
data |
A data frame where the rows represent cases and the columns the sets. Column names must be as in the formula. |
formula |
A string, list of strings or function representing a Boolean formula in disjunctive normal form |
Details
If formula is a function, it must take a data.frame and return
a vector.
If formula is a string or list of strings, the following conventions hold:
Set names must be capitalized in the formula and the data; if they are
lowercase, they are interpreted as the negation of the set.
If formula is a string, logical 'or' is expressed as a '+',
and logical 'and' as a '*'.
If formula is a list of strings, the strings are assumed to be
the dosjuncts and are concatenated with '+'.
The formula must be in disjunctive normal form, i.e. it must be a disjunction of
conjunctions of elementary or negated elementary sets. Example:
A*b*C + a*B
Value
the fuzzy set score of the set described by the formula for each case in the data
Examples
require(QCA)
data(d.urban)
evaluate_dnf(d.urban, "MLC*frb + CP")
Rewrite a list of clauses to a string containing a Boolean formula in disjunctive normal form
Description
Rewrite a list of clauses to a string containing a Boolean formula in disjunctive normal form
Usage
format_dnf(dnf)
Arguments
dnf |
list of clauses |
Value
string containing a Boolean formula in disjunctive normal form
Convert formula to function
Description
When given a Boolean formula (in disjunctive normal form, see details), this function produces a function that takes a data.frame of a QCA data table and computes the fuzzy set score for each case of membership in the set described by the formula
Usage
formula_to_function(formula)
Arguments
formula |
A string or vector of strings containing a Boolean formula in disjunctive normal form |
Details
Set names must be capitalized in the formula and the data; if they are
lowercase, they are interpreted as the negation of the set.
If formula is a string, logical 'or' is expressed as a '+',
and logical 'and' as a '*'.
If formula is a list of strings, the strings are assumed to be
the dosjuncts and are concatenated with '+'.
Disjunctive normal form means that the formula must be a disjunction of
conjunctions of elementary or negated elementary sets. Example:
A*b*C + a*B
Value
a function that takes a data.frame and computes the fuzzy set score of the set described by the formula for each case into a vector
Examples
formula_to_function("A*b*C + a*B")
Plot the fuzzy set scores of the solution and the outcome against each other
Description
Plot the fuzzy set scores of the solution and the outcome against each other
Usage
## S3 method for class 'qca'
plot(x, ...)
Arguments
x |
an object of class |
... |
further arguments passed on to |
Value
the ggplot plot object
Examples
## Not run:
require(QCA)
data(d.urban)
solution <- eqmcc(d.urban, outcome="RT", conditions=c("MLC", "FRB", "CP", "WSR"))
plot(solution)
## End(Not run)
Plot fuzzy set score of two sets against each other
Description
Plot fuzzy set score of two sets against each other
Usage
xyplot(x, y, data, labels = FALSE, main.diagonal = TRUE,
anti.diagonal = FALSE)
Arguments
x |
Formula that describes the fuzzy set to plot along the x axis |
y |
Formula that describes the fuzzy set to plot along the y axis |
data |
Data set of basic fuzzy set scores |
labels |
flag whether to label individual points with the case names |
main.diagonal |
flag whether to plot the main diagonal |
anti.diagonal |
flag whether to plot the anti diagonal |
Value
the ggplot plot object
Examples
require(QCA)
data(d.urban)
xyplot("MLC", "WSR", d.urban)