nu: Generic function for the latent variance of coefficients

In dynsurv: Dynamic Models for Survival Data

Generic function for the latent variance of coefficients

Description

Generic function for the latent variance of coefficients

Usage

nu(object, ...)

## S3 method for class 'bayesCox'
nu(object, ...)

Arguments

object	An object returned by function bayesCox.
...	Other arguments.

Value

A data.frame with 4 columns ("Iter", "Model", "Cov", "Value"), where Iter is the iteration number; Model and Cov contain the character values of the model type and covariates.

Methods (by class)

• nu(bayesCox): Extract Latent Variance from Bayesian Cox Model

  Extract latent variance of coefficients from bayesCox fitting results, and summarize them into a data frame. It is applicable when model="TimeVarying" or model="Dynamic", and coef.prior=list(type="HAR1").

  For details, see section on prior model in Wang (2013) and Wang (2014). The latent variance of coefficients in prior model was denoted as omega in Wang (2013).

References

X. Wang, M.-H. Chen, and J. Yan (2013). Bayesian dynamic regression models for interval censored survival data with application to children dental health. Lifetime data analysis, 19(3), 297–316.

X. Wang, X. Sinha, J. Yan, and M.-H. Chen (2014). Bayesian inference of interval-censored survival data. In: D. Chen, J. Sun, and K. Peace, Interval-censored time-to-event data: Methods and applications, 167–195.

See Also

bayesCox, and plotNu.

Examples

## See the examples in bayesCox.

dynsurv documentation built on Aug. 20, 2023, 1:07 a.m.