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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) <doi:10.1093/biomet/asn026> is used. Thus, the analysis does not rely on ad hoc identification.

Version: 2.0.0
Imports: lattice, plyr, reshape, plm, survey, lmtest, car, ISLR, AER, ggplot2, ChainLadder
Published: 2020-10-01
Author: Zoe Fannon, Bent Nielsen
Maintainer: Bent Nielsen <bent.nielsen at nuffield.ox.ac.uk>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
In views: ActuarialScience
CRAN checks: apc results

Documentation:

Reference manual: apc.pdf
Vignettes: Identification: illustrate and check identification used in plot fit function
Introduction: analysis of aggregate data
Introduction: analysis of individual data
Introduction: analysis of individual data: further examples
Generating new models from design matrix function
Reproducing HN2016
Reproducing KN2020
Illustrate and check identification used in plot fit function
Reproducing MMNN2016

Downloads:

Package source: apc_2.0.0.tar.gz
Windows binaries: r-devel: apc_2.0.0.zip, r-release: apc_2.0.0.zip, r-oldrel: apc_2.0.0.zip
macOS binaries: r-release (arm64): apc_2.0.0.tgz, r-oldrel (arm64): apc_2.0.0.tgz, r-release (x86_64): apc_2.0.0.tgz, r-oldrel (x86_64): apc_2.0.0.tgz
Old sources: apc archive

Reverse dependencies:

Reverse suggests: clmplus

Linking:

Please use the canonical form https://CRAN.R-project.org/package=apc to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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