| Type: | Package |
| Title: | Bayesian Estimation for Alpha-Mixture Survival Models |
| Version: | 0.1.0 |
| Description: | Implements Bayesian estimation and inference for alpha-mixture survival models, including Weibull and Exponential based components, with tools for simulation and posterior summaries. The methods target applications in reliability and biomedical survival analysis. The package implements Bayesian estimation for the alpha-mixture methodology introduced in Asadi et al. (2019) <doi:10.1017/jpr.2019.72>. |
| Maintainer: | Feng Luan <fluan1@niu.edu> |
| Imports: | MCMCpack, stats, utils, gtools |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.3 |
| LazyData: | true |
| LazyDataCompression: | xz |
| Suggests: | testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2025-10-17 19:22:24 UTC; feng |
| Author: | Feng Luan [aut, cre], Zhexuan Yang [aut], Duchwan Ryu [aut] |
| Depends: | R (≥ 3.5.0) |
| Repository: | CRAN |
| Date/Publication: | 2025-10-22 18:40:02 UTC |
Main Bayesian Mixture Model Function
Description
Main Bayesian Mixture Model Function
Usage
alpmixBayes(
d,
mcmc_values = NULL,
init_values = NULL,
prior = NULL,
survmodel = c("WW", "EW", "LL", "EWG"),
verbose = TRUE,
...
)
Arguments
d |
Input data |
mcmc_values |
MCMC parameters |
init_values |
Initial values |
prior |
Prior distributions |
survmodel |
Survival model type |
verbose |
Logical. If TRUE, progress messages are printed. Default is TRUE. |
... |
Additional arguments |
Value
Bayesian mixture model results
Run a demo of alpmixBayes
Description
This runs alpmixBayes on the packaged example dataset ewm1.100.
Usage
demo_run(verbose = TRUE)
Arguments
verbose |
Logical. If TRUE, progress messages are printed. Default is TRUE. |
Value
Summary of the Bayesian mixture model
Examples
# Run the demo (may take a few moments)
demo_run()
Error result handler
Description
Creates a structured error result when model fitting fails
Usage
error_result(model, message, verbose = TRUE)
Arguments
model |
Model type |
message |
Error message |
Value
Structured error result
EW Mixture Model Dataset
Description
Demonstration dataset for Exponential-Weibull mixture models. Contains 5 simulated datasets for examples and testing.
Usage
ew
Format
A list with 5 components, each containing mixture model data
Source
Simulated data
EWG Mixture Model Dataset
Description
Demonstration dataset for Exponential-Weibull-Gamma mixture models. Contains 5 simulated datasets for examples and testing.
Usage
ewg
Format
A list with 5 components, each containing:
Source
Simulated data
Examples
data(ewg)
str(ewg, max.level = 1)
# Extract data from first element
y_data <- ewg[[1]]$y
Exponential-Weibull-Gamma Mixture Model
Description
Exponential-Weibull-Gamma Mixture Model
Usage
ewgmix(d, init_values, mcmc_values, prior)
Arguments
d |
Input data |
init_values |
Initial values |
mcmc_values |
MCMC parameters |
prior |
Prior distributions |
Value
Model results
Exponential-Weibull Mixture Model
Description
Exponential-Weibull Mixture Model
Usage
ewmix(d, init_values, mcmc_values, prior)
Arguments
d |
Input data |
init_values |
Initial values |
mcmc_values |
MCMC parameters |
prior |
Prior distributions |
Value
Model results
Global variable declarations
Description
Declare global variables to avoid R CMD check notes
LL Mixture Model Dataset
Description
Demonstration dataset for Log-Logistic mixture models. Contains 5 simulated datasets for examples and testing.
Usage
ll
Format
A list with 5 components, each containing mixture model data
Source
Simulated data
Lognormal-Lognormal Mixture Model
Description
Lognormal-Lognormal Mixture Model
Usage
llmix(d, init_values, mcmc_values, prior)
Arguments
d |
Input data |
init_values |
Initial values |
mcmc_values |
MCMC parameters |
prior |
Prior distributions |
Value
Model results
Summary method for alpmixBayes objects
Description
Summary method for alpmixBayes objects
Usage
## S3 method for class 'alpmixBayes'
summary(object, ...)
Arguments
object |
An alpmixBayes object |
... |
Additional arguments passed to summary |
Value
A data frame with parameter estimates and credible intervals
WW Mixture Model Dataset
Description
Demonstration dataset for Weibull mixture models. Contains 5 simulated datasets for examples and testing.
Usage
ww
Format
A list with 5 components, each containing mixture model data
Source
Simulated data
Weibull-Weibull Mixture Model
Description
Weibull-Weibull Mixture Model
Usage
wwmix(d, init_values, mcmc_values, prior)
Arguments
d |
Input data |
init_values |
Initial values |
mcmc_values |
MCMC parameters |
prior |
Prior distributions |
Value
Model results