Package: bage 0.8.2

John Bryant

bage: Bayesian Estimation and Forecasting of Age-Specific Rates

Fast Bayesian estimation and forecasting of age-specific rates, probabilities, and means, based on 'Template Model Builder'.

Authors:John Bryant [aut, cre], Junni Zhang [aut], Bayesian Demography Limited [cph]

bage_0.8.2.tar.gz
bage_0.8.2.zip(r-4.5)bage_0.8.2.zip(r-4.4)bage_0.8.2.zip(r-4.3)
bage_0.8.2.tgz(r-4.4-x86_64)bage_0.8.2.tgz(r-4.4-arm64)bage_0.8.2.tgz(r-4.3-x86_64)bage_0.8.2.tgz(r-4.3-arm64)
bage_0.8.2.tar.gz(r-4.5-noble)bage_0.8.2.tar.gz(r-4.4-noble)
|bage.html✨
bage/json (API)
NEWS

# Install 'bage' in R:

install.packages('bage', repos = c('https://bayesiandemography.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bayesiandemography/bage/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

HFD - Components from Human Fertility Database
HMD - Components from Human Mortality Database
LFP - Components from OECD Labor Force Participation Data
isl_deaths - Deaths in Iceland
kor_births - Births in South Korea
nld_expenditure - Per Capita Health Expenditure in the Netherlands, 2003-2011
nzl_divorces - Divorces in New Zealand
nzl_households - People in One-Person Households in New Zealand
nzl_injuries - Fatal Injuries in New Zealand
usa_deaths - Accidental Deaths in the USA

On CRAN:

7.00 score 2 stars 38 scripts 164 downloads 41 exports 24 dependencies

Last updated 5 days agofrom:36bc66a706. Checks:ERROR: 4 OK: 5. Indexed: yes.

Target	Result	Date
Doc / Vignettes	FAIL	Nov 13 2024
R-4.5-win-x86_64	OK	Nov 13 2024
R-4.5-linux-x86_64	OK	Nov 13 2024
R-4.4-win-x86_64	OK	Nov 13 2024
R-4.4-mac-x86_64	OK	Nov 13 2024
R-4.4-mac-aarch64	OK	Nov 13 2024
R-4.3-win-x86_64	ERROR	Nov 13 2024
R-4.3-mac-x86_64	ERROR	Nov 13 2024
R-4.3-mac-aarch64	ERROR	Nov 13 2024

Exports:AR AR1 augment components computations equation fit forecast generate is_fitted Known Lin Lin_AR Lin_AR1 mod_binom mod_norm mod_pois N NFix replicate_data report_sim RW RW_Seas RW2 RW2_Infant RW2_Seas set_datamod_outcome_rr3 set_disp set_n_draw set_prior set_var_age set_var_sexgender set_var_time Sp SVD SVD_AR SVD_AR1 SVD_RW SVD_RW2 tidy unfit

Dependencies:cli cpp11 fansi generics glue lattice lifecycle magrittr Matrix matrixStats pillar pkgconfig poputils Rcpp RcppEigen rlang rvec sparseMVN tibble tidyselect TMB utf8 vctrs withr

Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.

Introduction

Rendered fromvig1_intro.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2024-09-27
Started: 2023-06-23

Mathematical Details

Rendered fromvig2_math.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2024-11-05
Started: 2023-06-23

Priors

Rendered fromvig3_priors.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2024-09-29
Started: 2023-06-23

Singular Value Decomposition

Rendered fromvig4_svd.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2024-09-27
Started: 2023-07-15

Bayesian Workflow

Rendered fromvig5_workflow.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2024-04-09
Started: 2023-06-23

Modelling Mortality

Rendered fromvig6_mortality.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2024-09-27
Started: 2023-07-15

Simulation

Rendered fromvig7_simulation.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2024-09-27
Started: 2024-09-27

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Autoregressive Prior	AR
Autoregressive Prior of Order 1	AR1
Extract Data and Modelled Values	augment.bage_mod
Extract Values for Hyper-Parameters	components.bage_mod
Extract Components used by SVD Summary	components.bage_ssvd
Information on Computations Performed Duration Model Fitting	computations
Data Models	datamods
Fit a Model	fit.bage_mod
Use a Model to Make a Forecast	forecast.bage_mod
Generate Values from Priors	generate.bage_prior_ar generate.bage_prior_known generate.bage_prior_norm generate.bage_prior_normfixed generate.bage_prior_rw generate.bage_prior_rw2 generate.bage_prior_rwseasfix
Generate Random Age or Age-Sex Profiles	generate.bage_ssvd
Components from Human Fertility Database	HFD
Components from Human Mortality Database	HMD
Test Whether a Model has Been Fitted	is_fitted
Deaths in Iceland	isl_deaths
Known Prior	Known
Births in South Korea	kor_births
Components from OECD Labor Force Participation Data	LFP
Linear Prior with Independent Normal Errors	Lin
Linear Prior with Autoregressive Errors	Lin_AR
Linear Prior with Autoregressive Errors of Order 1	Lin_AR1
Specify a Binomial Model	mod_binom
Specify a Normal Model	mod_norm
Specify a Poisson Model	mod_pois
Normal Prior	N
Normal Prior with Fixed Variance	NFix
Per Capita Health Expenditure in the Netherlands, 2003-2011	nld_expenditure
Divorces in New Zealand	nzl_divorces
People in One-Person Households in New Zealand	nzl_households
Fatal Injuries in New Zealand	nzl_injuries
Printing a Model	print.bage_mod
Priors for Intercept, Main Effects, Interactions	priors
Create Replicate Data	replicate_data
Simulation Study of a Model	report_sim
Random Walk Prior	RW
Random Walk Prior with Seasonal Effect	RW_Seas
Second-Order Random Walk Prior	RW2
Second-Order Random Walk Prior with 'Infant' Indicator	RW2_Infant
Second-Order Random Walk Prior with Seasonal Effect	RW2_Seas
Specify RR3 Data Model	set_datamod_outcome_rr3
Specify Prior for Dispersion or Standard Deviation	set_disp
Specify Number of Draws from Prior or Posterior Distribution	set_n_draw
Specify Prior for Model Term	set_prior
Specify Age Variable	set_var_age
Specify Sex or Gender Variable	set_var_sexgender
Specify Time Variable	set_var_time
P-Spline Prior	Sp
SVD-Based Prior for Age or Age-Sex Profiles	SVD
Dynamic SVD-Based Priors for Age Profiles or Age-Sex Profiles	SVD_AR SVD_AR1 SVD_RW SVD_RW2
Summarize Terms from a Fitted Model	tidy.bage_mod
Unfit a Model	unfit
Accidental Deaths in the USA	usa_deaths