R: Bayesian Mixture Log-Normal Survival Model

# Bayesian Mixture Log-Normal Survival Model

## Documentation for package ‘lnmixsurv’ version 3.1.7

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

augment.survival_ln_mixture | Augment data with information from a survival_ln_mixture object
augment.survival_ln_mixture_em | Augment data with information from a survival_ln_mixture_em object
fit_metrics | Function used to calculate some distance metrics between the predicted survival and the observed survival. 'fit_metrics()' is used to calculate distance metrics between empirical and fitted survival for a predictions object, preferably the object $preds returned from 'plot_fit_on_data()'.
join_empirical_hazard | Function used to join the empirical hazard to the data
nobs.survival_ln_mixture | Extract the number of observations from 'survival_ln_mixture' fit.
plot.survival_ln_mixture_em | Visualizes the path of the EM algorithm
plot_fit_on_data | Function used to quick visualize the fitted values (survival estimate) on the data used to fit the model (via EM algorithm or Gibbs).
predict.survival_ln_mixture | Predict from a Lognormal Mixture Model
predict.survival_ln_mixture_em | Predict from a lognormal_em Mixture Model fitted using EM algorithm.
simulate_data | Function to simulate survival data from a mixture of normal distribution.
sim_data | Simulated lognormal mixture data.
survival_ln_mixture | Lognormal mixture model - Gibbs sampler
survival_ln_mixture.default | Lognormal mixture model - Gibbs sampler
survival_ln_mixture.formula | Lognormal mixture model - Gibbs sampler
survival_ln_mixture_em | Lognormal mixture model - Expectation-Maximization Algorithm
survival_ln_mixture_em.default | Lognormal mixture model - Expectation-Maximization Algorithm
survival_ln_mixture_em.formula | Lognormal mixture model - Expectation-Maximization Algorithm
tidy.survival_ln_mixture | Tidying method for a Lognormal Mixture model.
tidy.survival_ln_mixture_em | Tidying method for a Lognormal Mixture model (fitted via Expectation-Maximization algorithm).