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cnaOpt  

Optimizing Consistency and Coverage in Configurational Causal Modeling
View on CRAN: Click here


Download and install cnaOpt package within the R console
Install from CRAN:
install.packages("cnaOpt")

Install from Github:
library("remotes")
install_github("cran/cnaOpt")

Install by package version:
library("remotes")
install_version("cnaOpt", "0.5.2")



Attach the package and use:
library("cnaOpt")
Maintained by
Mathias Ambuehl
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-10-21
Latest Update: 2022-07-08
Description:
This is an add-on to the 'cna' package comprising various functions for optimizing consistency and coverage scores of models of configurational comparative methods as Coincidence Analysis (CNA) and Qualitative Comparative Analysis (QCA). The function conCovOpt() calculates con-cov optima, selectMax() selects con-cov maxima among the con-cov optima, DNFbuild() can be used to build models actually reaching those optima, and findOutcomes() identifies those factor values in analyzed data that can be modeled as outcomes. For a theoretical introduction to these functions see Baumgartner and Ambuehl (2021) .
How to cite:
Mathias Ambuehl (2019). cnaOpt: Optimizing Consistency and Coverage in Configurational Causal Modeling. R package version 0.5.2, https://cran.r-project.org/web/packages/cnaOpt. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.1.0 (2019-10-21 16:10), 0.1.1 (2019-12-09 10:50), 0.2.0 (2020-09-14 11:10), 0.4.0 (2021-07-08 17:30), 0.5.0 (2021-12-17 17:00), 0.5.1 (2022-04-21 09:30)
Other packages that cited cnaOpt R package
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Other R packages that cnaOpt depends, imports, suggests or enhances
Complete documentation for cnaOpt
Functions, R codes and Examples using the cnaOpt R package
Some associated functions: cnaOpt . conCovOpt . conCovOpt_utils . ereduce . findOutcomes . selectMax . 
Some associated R codes: RcppExports.R . cnaOpt.R . conCovOpt.R . conCovOpt_utils.R . ereduce.R . findOutcomes.R .  Full cnaOpt package functions and examples
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