dlpl: First derivative of the Log Partial Likelihood.

In penMSM: Estimating Regularized Multi-state Models Using L1 Penalties

Description

Calculates the first partial derivative of the log partial likelihood with respect to the linear predictor.

Usage

dlpl(event, b, X, Ri, Ci)

Arguments

event	non-censoring event indicator.
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 first derivative of the log partial likelihood of a Cox type multistate model.

Value

A vector with the values of the partial first derivatives of the log partial likelihood with respect to the regression effects.

Author(s)

Holger Reulen

Examples

## Not run: dlpl(event, b, X, Ri, Ci)

penMSM documentation built on May 2, 2019, 11:06 a.m.