Bent Nielsen: Package apc

apc: Age-Period-Cohort Analysis

Functions for age-period-cohort analysis. Aggregate data can be organised in matrices indexed by age-cohort, age-period or cohort-period. The data can include dose and response or just doses. The statistical model is a generalized linear model (GLM) allowing for 3,2,1 or 0 of the age-period-cohort factors. Individual-level data should have a row for each individual and columns for each of age, period, and cohort. The statistical model for repeated cross-section is a generalized linear model. The statistical model for panel data is ordinary least squares. The canonical parametrisation of Kuang, Nielsen and Nielsen (2008) is used. Thus, the analysis does not rely on ad hoc identification.

Papers on Age-Period-Cohort Analysis

apc on CRAN

Version: 2.0
Published: 2020-10-01
Download: CRAN

apc: Development version

Version: 1.3.5
Published: 2019-11-27
Package source: apc_1.3.5.tar.gz
Windows binaries:

apc in Python

Jonas Harnau has written a version of apc in Python.


ReadData Illustrates how to read data from files and construct Uses the Belgian lung cancer data from Clayton and Schiffler (1987). Considers data store in csv format: response.csv, rates.csv and xlsx format: both.xlsx. 1.3 R code
Identification Illustrate and check identification used in plot fit function 1.1 PDF source R code
NewDesign Generating new models from design matrix function 1.1 PDF source R code
ReproducingMMNN2015 Reproducing Martinez Miranda, Nielsen and Nielsen (2015). Inference and forecasting in the age-period-cohort model with unknown exposure with an application to mesothelioma mortality. Journal of the Royal Statistical Society series A 178, 29-55. Download: Published version. Nuffield DP. Estimation, forecasting using data.asbestos() 1.2.2 PDF source R code
ReproducingMMNN2016 Reproducing Martinez-Miranda, Nielsen and Nielsen (2016). A simple benchmark for mesothelioma projection for Great Britain. Occupational and Environmental Medicine 73, 561-563. Download: Published version. Nuffield DP. Estimation, forecasting using data.asbestos.2013() 1.2.1 PDF source R code
ReproducingHN2016 Reproducing Harnau and Nielsen (2018). Asymptotic theory for over-dispersed age-period-cohort and extended chain ladder models. Journal of the American Statistical Association 113, 1722-1732. Download: Published version. Nuffield DP. Estimation, forecasting using data.loss.TA() 1.3.2 PDF source R code
ReproducingKN2018 Reproducing Kuang and Nielsen (2020). Generalized log normal Chain-Ladder models. Scandinavian Actuarial Journal 2020, 553--576. Download: Open access. Nuffield DP. Estimation, forecasting using data.loss.XL() 1.3.5 PDF source R code

apc: Development Versions, Previous Releases

Version: 1.3.4
Published: 2019-11-18
Package source: apc_1.3.4.tar.gz
Windows binaries:

Version: 1.3.3
Published: 2018-08-27
Package source: apc_1.3.3.tar.gz
Windows binaries:
R file: combined.functions.R Script file with the updates. Run this as a script file if working with an earlier version of apc.

Version: 1.3.2
Published: 2018-08-15
Package source: apc_1.3.2.tar.gz
Windows binaries:

Version: 1.3.1
Published: 2017-05-07
Package source: apc_1.3.1.tar.gz
Windows binaries:

Version: 1.3
Published: 2016-12-01
Download: CRAN