bjimpute: ELMSurv bjimpute
In whcsu/ELMSurv: Extreme Learning Machine for Survival Analysis
Description
Usage
Arguments
Value
Author(s)
References
See Also
Description
A Buckley-James Esitmator
Usage
1
bjimpute(y, cen, x, inibeta)
Arguments
y
Survival time of training data.
cen
The censoring indicator of training data.
x
The covariates(predictor variables) of training data.
inibeta
Initial values set for Buckley-James Imputation.
Value
Imputed survival times
Author(s)
Hong Wang
References
Hong Wang et al (2017). A Survival Ensemble of Extreme Learning Machine. Applied Intelligence, in press.
See Also
whcsu/ELMSurv documentation built on May 6, 2019, 5:04 p.m.
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Description Usage Arguments Value Author(s) References See Also
Description
A Buckley-James Esitmator
Usage
1 | bjimpute(y, cen, x, inibeta)
|
Arguments
y |
Survival time of training data. |
cen |
The censoring indicator of training data. |
x |
The covariates(predictor variables) of training data. |
inibeta |
Initial values set for Buckley-James Imputation. |
Value
Imputed survival times
Author(s)
Hong Wang
References
Hong Wang et al (2017). A Survival Ensemble of Extreme Learning Machine. Applied Intelligence, in press.
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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