nv.krls: Estimating Normal Vector through Kernel Regularized Least...
In gentok/ipbridging: Bridging Ideal Point Estimates
Description
Usage
Arguments
Value
Author(s)
References
See Also
Description
Estimating Normal Vector through Kernel Regularized Least Squares
Usage
1
Arguments
xmat
Matrix of OC coordinates (i.e., predictors).
resp
Response Variable (i.e., ordered choices).
sample.size
Sample size for data used for the estimation of KRLS.
...
Additional arguments passed to krls.
Value
A vector of coefficients.
Author(s)
Tzu-Ping Liu jamesliu0222@gmail.com, Gento Kato gento.badger@gmail.com, and Sam Fuller sjfuller@ucdavis.edu.
This is a modified version of the code included in ooc function.
References
Jeremy Ferwerda, Jens Hainmueller, Chad J. Hazlett (2017). Kernel-Based Regularized Least Squares in R (KRLS) and Stata (krls). Journal of Statistical Software, 79(3), 1-26. doi:10.18637/jss.v079.i03
See Also
gentok/ipbridging documentation built on March 29, 2020, 3:06 a.m.
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Description Usage Arguments Value Author(s) References See Also
Description
Estimating Normal Vector through Kernel Regularized Least Squares
Usage
1 |
Arguments
xmat |
Matrix of OC coordinates (i.e., predictors). |
resp |
Response Variable (i.e., ordered choices). |
sample.size |
Sample size for data used for the estimation of KRLS. |
... |
Additional arguments passed to |
Value
A vector of coefficients.
Author(s)
Tzu-Ping Liu jamesliu0222@gmail.com, Gento Kato gento.badger@gmail.com, and Sam Fuller sjfuller@ucdavis.edu.
This is a modified version of the code included in ooc function.
References
Jeremy Ferwerda, Jens Hainmueller, Chad J. Hazlett (2017). Kernel-Based Regularized Least Squares in R (KRLS) and Stata (krls). Journal of Statistical Software, 79(3), 1-26. doi:10.18637/jss.v079.i03
See Also
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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