ggresiduals

Parametric survival regression models under the maximum likelihood approach via 'Stan'. Implemented regression models include accelerated failure time models, proportional hazards models, proportional odds models, accelerated hazard models, Yang and Prentice models, and extended hazard models. Available baseline survival distributions include exponential, Weibull, log-normal, log-logistic, gamma, generalized gamma, rayleigh, Gompertz and fatigue (Birnbaum-Saunders) distributions. References: Lawless (2002) <ISBN:9780471372158>; Bennett (1982) <doi:10.1002/sim.4780020223>; Chen and Wang(2000) <doi:10.1080/01621459.2000.10474236>; Demarqui and Mayrink (2021) <doi:10.1214/20-BJPS471>.

Fabio Demarqui

survstan

Fitting Survival Regression Models via 'Stan'

Andrew Johnson

ggresiduals function

<dl><dt>object</dt>
<dd>a fitted model object.</dd>
<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd></dl>

Arguments

Generic S3 method ggresiduals — ggresiduals

<dl>

<dt>object</dt>
<dd>a fitted model object.</dd>


<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd>

</dl>

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ggresiduals: Generic S3 method ggresiduals

Description

Usage

Value

Arguments

Details