scorevectorP: Score vector of the Poisson log likelihood.
In penMSM: Estimating Regularized Multi-state Models Using L1 Penalties
Description
Usage
Arguments
Details
Value
Author(s)
Examples
Description
This function calculates the score vector needed for the
estimation of multistate models using the Fisher scoring algorithm.
Usage
1
scorevectorP(mu, X, event)
Arguments
mu
mu.
X
design matrix.
event
non-censoring event indicator.
Details
This function implements the score vector (i.e., the
first partial derivative of the Poisson log likelihood with respect
to the components of the regression effect vector beta).
Value
Score vector scorevector.
Author(s)
Holger Reulen
Examples
1
## Not run: scorevectorP(beta, X, event)
Example output
penMSM documentation built on May 2, 2019, 11:06 a.m.
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Description Usage Arguments Details Value Author(s) Examples
Description
This function calculates the score vector needed for the estimation of multistate models using the Fisher scoring algorithm.
Usage
1 | scorevectorP(mu, X, event)
|
Arguments
mu |
mu. |
X |
design matrix. |
event |
non-censoring event indicator. |
Details
This function implements the score vector (i.e., the
first partial derivative of the Poisson log likelihood with respect
to the components of the regression effect vector beta).
Value
Score vector scorevector.
Author(s)
Holger Reulen
Examples
1 | ## Not run: scorevectorP(beta, X, event)
|
Example output
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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