llP: Log Likelihood for Poisson Regression.
In penMSM: Estimating Regularized Multi-state Models Using L1 Penalties
Description
Usage
Arguments
Details
Value
Author(s)
Examples
Description
Calculates the log likelihood for poisson regression.
Usage
1
Arguments
beta
vector of regression coefficients.
X
design matrix.
event
non-censoring event indicator.
offset
offset.
Details
This function calculates the Poisson log likelihood.
Value
The values of the Poisson log likelihood.
Author(s)
Holger Reulen
Examples
1
## Not run: llP(beta, X, event, offset)
penMSM documentation built on May 2, 2019, 11:06 a.m.
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Description Usage Arguments Details Value Author(s) Examples
Description
Calculates the log likelihood for poisson regression.
Usage
1 |
Arguments
beta |
vector of regression coefficients. |
X |
design matrix. |
event |
non-censoring event indicator. |
offset |
offset. |
Details
This function calculates the Poisson log likelihood.
Value
The values of the Poisson log likelihood.
Author(s)
Holger Reulen
Examples
1 | ## Not run: llP(beta, X, event, offset)
|
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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