bage-package: Package 'bage'

In bage: Bayesian Estimation and Forecasting of Age-Specific Rates

Package 'bage'

Description

Bayesian estimation and forecasting of age-specific rates. Estimation uses TMB, and is fast.

Example workflow

1. Specify model using mod_pois()

2. Fit model using fit()

3. Extract results using augment()

4. Check model using replicate_data()

Functions

Specify model

• mod_pois() Specify a Poisson model

• mod_binom() Specify a binomial model

• mod_norm() Specify a normal model

• set_prior() Specify prior for main effect or interaction

• priors Overview of priors for main effects or interactions

• set_disp() Specify prior for dispersion/variance

• set_covariates() Add covariates to model

• datamods Overview of data models (measurement error models)

• confidential Overview of confidentialization models

Fit model

• fit() Derive posterior distribution

Extract results

• augment() Original data, plus observation-level estimates

• components() Hyper-parameters

• dispersion() Dispersion parameter (a type of hyper-parameter)

• tidy() One-line summary

• set_n_draw() Specify number of prior or posterior draws

Forecast

• forecast() Use model to obtain estimates for future periods

Check model

• replicate_data() Compare real and simulated data

• report_sim() Simulation study of model

Data

• datasets Overview of datasets

• svds Overview of scaled SVDs

Author(s)

Maintainer: John Bryant [e-mail]

Authors:

• Junni Zhang [e-mail]

Other contributors:

• Bayesian Demography Limited [copyright holder]

See Also

Useful links:

• https://bayesiandemography.github.io/bage/

• https://github.com/bayesiandemography/bage

• Report bugs at https://github.com/bayesiandemography/bage/issues

bage documentation built on Nov. 19, 2025, 9:07 a.m.