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crov
View on CRAN: Click
here
Download and install crov package within the R console
Install from CRAN:
install.packages("crov")
Install from Github:
library("remotes")
install_github("cran/crov") Install by package version:
library("remotes")
install_version("crov", "0.3.0") Attach the package and use:
library("crov")
Maintained by
Javier Espinosa
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-11-02
Latest Update: 2023-08-25
Description:
Fits a constrained regression model for an ordinal response with ordinal predictors and possibly others, Espinosa and Hennig (2019) . The parameter estimates associated with an ordinal predictor are constrained to be monotonic. If a monotonicity direction (isotonic or antitonic) is not specified for an ordinal predictor by the user, then one of the available methods will either establish it or drop the monotonicity assumption. Two monotonicity tests are also available to test the null hypothesis of monotonicity over a set of parameters associated with an ordinal predictor.
How to cite:
Javier Espinosa (2018). crov: Constrained Regression Model for an Ordinal Response and Ordinal Predictors. R package version 0.3.0, https://cran.r-project.org/web/packages/crov. Accessed 08 Aug. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for crov
Functions, R codes and Examples using
the crov R package
Some associated functions: confRegCCR . confRegUCRandUCCR . crovData . mdcp . monoTestBonf . monoTestConfReg . plotCMLE .
Some associated R codes: cmleBonferroni.R . cmleConfReg.R . cmleFiltered.R . confRegCCR.R . confRegUCRandUCCR.R . createConstraints.R . loglikGrad.R . loglikHess.R . loglikOrdPred.R . mdcp.R . mdcs1.R . mdcs2.R . monoTestBonf.R . monoTestBonfSingle.R . monoTestConfReg.R . plotCMLE.R . realDataExample.R . Full crov package functions and examples
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