penMSM (version 0.99)

Estimating Regularized Multi-state Models Using L1 Penalties

Description

Structured fusion Lasso penalized estimation of multi-state models with the penalty applied to absolute effects and absolute effect differences (i.e., effects on transition-type specific hazard rates).

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Version

Install

install.packages('penMSM')

Monthly Downloads

225

Version

0.99

License

GPL (>= 2)

Maintainer

Holger Reulen

Last Published

January 12th, 2015

Functions in penMSM (0.99)

dlpl

First derivative of the Log Partial Likelihood.

lpl

Log Partial Likelihood.

dpenaltyfunction

First derivative of the penalty function.

ddlpl

ddlpl.

buildrisksets

Calculation of risksets needed for partial likelihood formulation of multistate models.

penaltymatrix

Penalty matrix for L1 penalized estimation of multistate models.

dapproxpenalty

First derivative of the locally quadratic approximated penalty.

plmatrix

plmatrix.

llP

Log Likelihood for Poisson Regression.

penMSM

penMSM.

scorevectorP

Score vector of the Poisson log likelihood.

Score vector and Fisher information matrix of the Poisson log likelihood.

fisherinfo

Fisher information matrix of the log partial likelihood of a multistate model.

fishercpp

Fisher information matrix of the log partial likelihood of a multistate model.

scorevector

Score vector of the log partial likelihood of a multistate model.

fisherinfoP

Fisher information matrix of the Poisson log likelihood.