The implemented method uses for smoothing bivariate thin plate splines, bivariate lasso-type regularization, and allows for both period and cohort effects. Thus the mortality rates are modelled as the sum of four components: a smooth bivariate function of age and time, smooth one-dimensional cohort effects, smooth one-dimensional period effects and random errors.

Install the latest version of this package by entering the following in R:

`install.packages("smoothAPC")`

Author | Alexander Dokumentov, Rob J Hyndman |

Date of publication | 2016-09-18 12:59:47 |

Maintainer | Alexander Dokumentov <alexander.dokumentov@gmail.com> |

License | GPL (>= 2) |

Version | 0.1 |

https://bitbucket.org/alexanderdokumentov/smoothapcpackage |

**autoSmoothAPC:** Smooths demographic data using automatically estimated...

**plot3d:** Presents data as a 3D surface

**plot3d.matrix:** Presents matrix as a 3D surface

**plot3d.smAPC:** Presents demographic data as a 3D surface

**plot.matrix:** Presents matrix as a heatmap

**plot.smAPC:** Presents demographic data as a heatmap

**signifAutoSmoothAPC:** Smooths demographic data using automatically estimated...

**smoothAPC:** Smooths demographic data optionally taking into account...

tests

tests/testthat.R
tests/testthat

tests/testthat/test_estPar.R
tests/testthat/test_twoStepDemogSmooth.R
tests/testthat/test_autoDemogSmooth.R
tests/testthat/test_demogSmooth.R
NAMESPACE

R

R/cv.R
R/show.R
R/diags.R
R/print.R
R/auto.l1tp.smooth.R
R/l1tp.smooth.R
MD5

DESCRIPTION

man

man/plot.smAPC.Rd
man/plot3d.Rd
man/autoSmoothAPC.Rd
man/plot.matrix.Rd
man/plot3d.smAPC.Rd
man/plot3d.matrix.Rd
man/smoothAPC.Rd
man/signifAutoSmoothAPC.Rd
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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

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

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