CoxMain: The main function using block-wise mm-boosting algorithm
In LingfengLuo0510/CoxAdditive: Block-wise gradient boosting algorithm on cox additive models
Description
Usage
Arguments
Value
Description
The main function using block-wise mm-boosting algorithm
Usage
1
2
Arguments
delta
event indicator
z
Covariate matrix
time
the death time
p
number of variables
N
the sample size
knot
the number of basis functions for non-linear predictors
maxit
the number of maximum iterations
rate
the learning rate
tol
the convergence threshold
Value
return a list of the following values
*beta : 1 denotes selected variables and 0 denotes unselected variables.
*time : the used time
*convergence : whether it's converge within maximum iteration steps
*key : the number of iterations
LingfengLuo0510/CoxAdditive documentation built on May 7, 2019, 6:56 p.m.
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Description Usage Arguments Value
Description
The main function using block-wise mm-boosting algorithm
Usage
1 2 |
Arguments
delta |
event indicator |
z |
Covariate matrix |
time |
the death time |
p |
number of variables |
N |
the sample size |
knot |
the number of basis functions for non-linear predictors |
maxit |
the number of maximum iterations |
rate |
the learning rate |
tol |
the convergence threshold |
Value
return a list of the following values *beta : 1 denotes selected variables and 0 denotes unselected variables. *time : the used time *convergence : whether it's converge within maximum iteration steps *key : the number of iterations
R Package Documentation
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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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