apc: Age-Period-Cohort Analysis
Version 1.3

Functions for age-period-cohort analysis. The 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. The canonical parametrisation of Kuang, Nielsen and Nielsen (2008) is used. Thus, the analysis does not rely on ad hoc identification.

AuthorBent Nielsen
Date of publication2016-12-01 08:28:22
MaintainerBent Nielsen <bent.nielsen@nuffield.ox.ac.uk>
LicenseGPL-3
Version1.3
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("apc")

Popular man pages

apc.data.sums: Computes age, period and cohort sums of a matrix
apc.fit.model: Fits an age period cohort model
apc.forecast.apc: Forecast models with APC structure.
apc.plot.data.all: Make all descriptive plots.
data.asbestos: Asbestos data
data.Belgian.lung.cancer: Belgian lung cancer data
internal: Internal apc Functions
See all...

All man pages Function index File listing

Man pages

apc_1.3-package: Age-period-cohort analysis
apc.data.list: Arrange data as an apc.data.list
apc.data.list.subset: Cut age, period and cohort groups from data set.
apc.data.sums: Computes age, period and cohort sums of a matrix
apc.fit.model: Fits an age period cohort model
apc.forecast: Forecasts from age-period-cohort models.
apc.forecast.ac: Forecast for Poisson response model with AC structure.
apc.forecast.ap: Forecast for Poisson response model with AP structure.
apc.forecast.apc: Forecast models with APC structure.
apc.get.design: Create design matrices
apc.get.index: Get indices for mapping data into trapezoid formation
apc.identify: Identification of time effects
apc.plot.data.all: Make all descriptive plots.
apc.plot.data.level: Level plot of data matrix.
apc.plot.data.sparsity: This plot shows heat map of the sparsity of a data matrix.
apc.plot.data.sums: This plot shows sums of data matrix by age, period or cohort.
apc.plot.data.within: This plot shows time series of matrix within age, period or...
apc.plot.fit: Plots of apc estimates
apc.plot.fit.all: Make all fit plots.
apc.plot.fit.pt: Plot probability transform of responses given fitted values
apc.plot.fit.residuals: Level plots of residuals / fitted values / linear predictors
apc.polygon: Add connected line and standard deviation polygons to a plot
data.aids: UK aids data
data.asbestos: Asbestos data
data.Belgian.lung.cancer: Belgian lung cancer data
data.Italian.bladder.cancer: Italian bladder cancer data
data.Japanese.breast.cancer: Japanese breast cancer data
data.loss.BZ: Motor data
data.loss.TA: Motor data
data.loss.VNJ: Motor data
data.RH.mortality: 2-sample mortality data.
data.US.prostate.cancer: Japanese breast cancer data
internal: Internal apc Functions
vector.2.triangle: Organise vector as matrix with triangle structure

Functions

apc Man page
apc-package Man page
apc.data.list Man page Source code
apc.data.list.subset Man page Source code
apc.data.sums Man page Source code
apc.fit.model Man page Source code
apc.fit.table Man page Source code
apc.forecast Man page
apc.forecast.ac Man page Source code
apc.forecast.ap Man page Source code
apc.forecast.apc Man page Source code
apc.get.design Man page Source code
apc.get.design.collinear Man page Source code
apc.get.index Man page Source code
apc.identify Man page Source code
apc.internal.function.date.2.character Man page Source code
apc.plot.data.all Man page Source code
apc.plot.data.level Man page Source code
apc.plot.data.sparsity Man page Source code
apc.plot.data.sums Man page Source code
apc.plot.data.within Man page Source code
apc.plot.data.within.all.six Man page Source code
apc.plot.fit Man page Source code
apc.plot.fit.all Man page Source code
apc.plot.fit.fitted.values Man page Source code
apc.plot.fit.linear.predictors Man page Source code
apc.plot.fit.pt Man page Source code
apc.plot.fit.residuals Man page Source code
apc.polygon Man page Source code
data.Belgian.lung.cancer Man page Source code
data.Italian.bladder.cancer Man page Source code
data.Japanese.breast.cancer Man page Source code
data.RH.mortality Man page
data.RH.mortality.dk Man page Source code
data.RH.mortality.no Man page Source code
data.US.prostate.cancer Man page Source code
data.aids Man page Source code
data.asbestos Man page Source code
data.asbestos.2013 Man page Source code
data.asbestos.2013.men Man page Source code
data.asbestos.2013.women Man page Source code
data.loss.BZ Man page Source code
data.loss.TA Man page Source code
data.loss.VNJ Man page Source code
foo2 Man page
foo3 Man page
foo4 Man page
vector.2.triangle Man page Source code

Files

inst
inst/doc
inst/doc/Vignettes.Rnw
inst/doc/Vignettes.pdf
NAMESPACE
NEWS
R
R/apc_data.R
R/apc_plot_data.R
R/apc_forecast.R
R/apc_data_sets.R
R/apc_identify.R
R/internal.R
R/apc_get_index.R
R/apc_fit.R
R/apc_plot_fit.R
vignettes
vignettes/Vignettes.Rnw
MD5
build
build/vignette.rds
DESCRIPTION
man
man/apc.plot.fit.pt.Rd
man/apc.polygon.Rd
man/data.loss.TA.Rd
man/data.loss.VNJ.Rd
man/apc.plot.fit.Rd
man/internal.Rd
man/apc.forecast.apc.Rd
man/data.asbestos.Rd
man/apc.data.list.Rd
man/apc.plot.data.within.Rd
man/data.Japanese.breast.cancer.Rd
man/data.loss.BZ.Rd
man/apc.plot.data.level.Rd
man/apc.plot.data.all.Rd
man/data.Belgian.lung.cancer.Rd
man/data.aids.Rd
man/data.US.prostate.cancer.Rd
man/data.RH.mortality.Rd
man/apc.forecast.Rd
man/apc_1.3-package.Rd
man/apc.identify.Rd
man/apc.forecast.ac.Rd
man/vector.2.triangle.Rd
man/apc.forecast.ap.Rd
man/apc.data.sums.Rd
man/apc.plot.fit.all.Rd
man/apc.fit.model.Rd
man/data.Italian.bladder.cancer.Rd
man/apc.plot.fit.residuals.Rd
man/apc.get.design.Rd
man/apc.data.list.subset.Rd
man/apc.get.index.Rd
man/apc.plot.data.sums.Rd
man/apc.plot.data.sparsity.Rd
apc documentation built on May 19, 2017, 12:14 p.m.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs in the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.