directCalibration: Calibration in fuzzy set QCA.
In QCA3: Yet another package for Qualitative Comparative Analysis
Description
Usage
Arguments
Details
Value
Author(s)
References
Examples
Description
Direct method of calibration in fuzzy set QCA.
Usage
1
2
directCalibration(x, fullin, fullout, crossover, infz = 0.953,
outfz = 0.047, details = FALSE)
Arguments
x
an interval variable to be converted to fuzzy set score.
fullin
scalar indicating full membership.
fullout
scalar indicating the full non-membership.
crossover
scalar indicating cross over point.
infz
fuzzy set score of full membership, corresponding to fullin.
outfz
fuzzy set score of full non-membership, corresponding to fullout.
details
logical.
Details
Usually, the sum of infz and outfz should be 1. In Ragin (2008), infz
is 0.953 and outfz is 0.047, which lead to the log odd of membership
being (proximitely) 3.0 and -3.0.
Value
When details is TRUE, it the result is a data frame. Otherwise, the
value is a numeric vector of fuzzy set score.
Author(s)
Ronggui HUANG
References
Ragin, Charles C. 2008. "Redesigning social inquiry: fuzzy sets and
beyond." Chapter 5. Chicago: University of Chicago Press.
Examples
1
directCalibration(Lipset_fs$Developed,800,300,550)
QCA3 documentation built on May 2, 2019, 4:49 p.m.
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Description Usage Arguments Details Value Author(s) References Examples
Description
Direct method of calibration in fuzzy set QCA.
Usage
1 2 | directCalibration(x, fullin, fullout, crossover, infz = 0.953,
outfz = 0.047, details = FALSE)
|
Arguments
x |
an interval variable to be converted to fuzzy set score. |
fullin |
scalar indicating full membership. |
fullout |
scalar indicating the full non-membership. |
crossover |
scalar indicating cross over point. |
infz |
fuzzy set score of full membership, corresponding to fullin. |
outfz |
fuzzy set score of full non-membership, corresponding to fullout. |
details |
logical. |
Details
Usually, the sum of infz and outfz should be 1. In Ragin (2008), infz is 0.953 and outfz is 0.047, which lead to the log odd of membership being (proximitely) 3.0 and -3.0.
Value
When details is TRUE, it the result is a data frame. Otherwise, the value is a numeric vector of fuzzy set score.
Author(s)
Ronggui HUANG
References
Ragin, Charles C. 2008. "Redesigning social inquiry: fuzzy sets and beyond." Chapter 5. Chicago: University of Chicago Press.
Examples
1 | directCalibration(Lipset_fs$Developed,800,300,550)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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