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multiRec (version 1.0.6)

Analysis of Multi-Type Recurrent Events

Description

Implements likelihood-based estimation and diagnostics for multi-type recurrent event data with dynamic risk that depends on prior events and accommodates terminating events. Methods are described in Ghosh, Chan, Younes and Davis (2023) "A Dynamic Risk Model for Multitype Recurrent Events" .

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Version

Install

install.packages('multiRec')

Version

1.0.6

License

GPL-2

Maintainer

Alokananda Ghosh

Last Published

February 3rd, 2026

Functions in multiRec (1.0.6)

Inverse Yeo-Johnson link

Yeo-Johnson transformation with parameter k

Issue a warning

Fit the multi-type recurrent event model

Simulated dataset with two types of multi-type recurrent events

deviance.multiRec

Deviance of a fitted model

Akaike's Information Criterion

identityInvLink

Identity inverse link

confint.multiRec

Confidence Intervals for Model Parameters

Bayesian Information Criteron

logLik.multiRec

Log likelihood of a fitted model

Plot profile likelihoods

Residuals from a fitted model

Issue an error message and stop

Issue an error message and stop

Simulated dataset with four types of multi-type recurrent events

Get starting values for proportional hazards style likelihood

Return the number of indices assigned so far

Return a vector of indices

Log Inverse link

Collapse a vector into a string

Print a short summary of the model fit

Return the parameter vector

resetParamVector

Initialize an empty parameter vector

Calculate the likelihood)

Reset the index offset

Inverse Yeo-Johnson transformation with parameter k

Construct a object returned by multiRec

Variance covariance matrix of a fitted model

Collapse a vector into a string

Set a part of the parameter vector

Set names for a part of the parameter vector

Yeo-Johnson link