ddlpl: ddlpl.
In penMSM: Estimating Regularized Multi-state Models Using L1 Penalties
Description
Usage
Arguments
Details
Value
Author(s)
Examples
Description
Second partial derivative of the log partial likelihood
with respect to the linear predictor.
Usage
1
ddlpl(b, X, Ri, Ci)
Arguments
b
vector of regression coefficients.
X
design matrix.
Ri
list of length n with vectors as list elements,
with the i-th element being the riskset belonging to the i-th spell.
Ci
list of length n with vectors as list elements,
with the i-th element capturing the indexes of risksets in which spell
i is included.
Details
This function calculates the second partial derivative of the log partial likelihood.
Value
A vector with second gradients.
Author(s)
Holger Reulen
Examples
1
## Not run: ddlpl(b, X, Ri, Ci)
penMSM documentation built on May 2, 2019, 11:06 a.m.
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Description Usage Arguments Details Value Author(s) Examples
Description
Second partial derivative of the log partial likelihood with respect to the linear predictor.
Usage
1 | ddlpl(b, X, Ri, Ci)
|
Arguments
b |
vector of regression coefficients. |
X |
design matrix. |
Ri |
list of length |
Ci |
list of length |
Details
This function calculates the second partial derivative of the log partial likelihood.
Value
A vector with second gradients.
Author(s)
Holger Reulen
Examples
1 | ## Not run: ddlpl(b, X, Ri, Ci)
|
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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