From 63a17dc3789e97fa12908206ea1d96e068fbdbb7 Mon Sep 17 00:00:00 2001
From: Reinhold Kainhofer <reinhold@kainhofer.com>
Date: Fri, 27 Oct 2023 10:02:30 +0200
Subject: [PATCH] V2.0.5: Update README, use Rmd
---
.Rbuildignore | 1 +
DESCRIPTION | 6 +-
NEWS.md | 1 +
README.Rmd | 145 ++++++++++++++++++
README.md | 247 ++++++++++++++++++++----------
man/MortalityTables-package.Rd | 4 +-
man/figures/README-Plotting-1.png | Bin 0 -> 13296 bytes
man/figures/README-Plotting-2.png | Bin 0 -> 12672 bytes
man/figures/README-Plotting-3.png | Bin 0 -> 11647 bytes
9 files changed, 321 insertions(+), 83 deletions(-)
create mode 100644 README.Rmd
create mode 100644 man/figures/README-Plotting-1.png
create mode 100644 man/figures/README-Plotting-2.png
create mode 100644 man/figures/README-Plotting-3.png
diff --git a/.Rbuildignore b/.Rbuildignore
index 68081ee..6e9b8ed 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -12,3 +12,4 @@ PossibleTables.txt
^inst/extdata/Austria_Population_Observation.csv$
^revdep$
^cran-comments\.md$
+^README\.Rmd$
diff --git a/DESCRIPTION b/DESCRIPTION
index bf8af93..b0a59db 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -3,8 +3,8 @@ Type: Package
Version: 2.0.5
Date: 2023-10-27
Title: A Framework for Various Types of Mortality / Life Tables
-Authors@R: c(person("Reinhold", "Kainhofer", role=c("aut", "cre"), email="reinhold@kainhofer.com"))
-Author: Reinhold Kainhofer [aut, cre]
+Authors@R: c(person("Reinhold", "Kainhofer", role=c("aut", "cre", "cph"), email="reinhold@kainhofer.com"))
+Author: Reinhold Kainhofer [aut, cre, cph]
Maintainer: Reinhold Kainhofer <reinhold@kainhofer.com>
URL: https://gitlab.open-tools.net/R/r-mortality-tables
BugReports: https://gitlab.open-tools.net/R/r-mortality-tables/-/issues
@@ -25,7 +25,7 @@ Suggests:
tidyverse,
reshape2,
rmarkdown
-Description: Classes to implement and plot cohort life tables
+Description: Classes to implement, analyze and plot cohort life tables
for actuarial calculations. Birth-year dependent cohort mortality
tables using a yearly trend to extrapolate from a base year are implemented,
as well as period life table, cohort life tables using an age shift, and
diff --git a/NEWS.md b/NEWS.md
index 5ef791b..796ffef 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,6 +1,7 @@
# MortalityTables 2.0.5 (27.10.2023):
* Fix incorrect ages in Austrian population mortality
+ * Update README with examples
# MortalityTables 2.0.4 (19.10.2023):
* Add new Austrian population mortality tables (2020/22)
diff --git a/README.Rmd b/README.Rmd
new file mode 100644
index 0000000..88b092a
--- /dev/null
+++ b/README.Rmd
@@ -0,0 +1,145 @@
+---
+output: github_document
+---
+
+<!-- README.md is generated from README.Rmd. Please edit that file -->
+
+```{r, include = FALSE}
+knitr::opts_chunk$set(
+ collapse = TRUE,
+ comment = "#>",
+ fig.path = "man/figures/README-",
+ out.width = "100%"
+)
+library(tidyverse)
+library(reshape2)
+library(pracma)
+```
+
+# MortalityTables
+
+<!-- badges: start -->
+<!-- badges: end -->
+
+The goal of MortalityTables is to provide generic base classes and functions to
+handle all kinds of actuarial actuarial mortality tables (period and cohort life tables).
+Cohort and static life tables are implemented, observed data can be used, and
+existing life tables can be blended or extrapolated to derive new tables.
+
+Furthermore, plotting functions are provided for reports and publications.
+
+## Installation
+
+You can install the development version of MortalityTables from [GitHub](https://github.com/) with:
+
+``` r
+# install.packages("devtools")
+devtools::install_github("kainhofer/MortalityTables")
+```
+
+## About the package
+
+The MortalityTables package provides the `mortalityTable` base class and
+some derived classes to handle different types of mortality tables (also
+called life tables), mainly
+used for life insurance. Additionally it provides a plot function to compare
+multiple life tables either directly using the absolute mortalities in
+log-linear plots or using relative mortalities as percentages of a given
+reference table.
+
+### Types of Life Tables
+
+Provided types of mortality tables are:
+
+* Base class
+: Class `mortalityTable`
+* Period life table
+: Class `mortalityTable.period(ages, deathProbs, ..., baseYear=2000)`
+: Death probabilities observed / predicted for one observation year;
+No dependency on the bith year is assumed.
+* Cohort life table using age-specific trends
+: Class `mortalityTable.trendProjection`
+: Death probabilities of a given base year are projected into the future
+using age-specific trends $\lambda_x$. The death probability of an $x$-year old in year
+`baseYear + n` is calculated as:
+ $$q_x^{(baseYear+n)} = q_x^{(baseYear)} \cdot e^{-n\cdot\lambda_x}$$
+ : Consequently, the death probabilities for a person born in year `YOB` can be calculated as
+$$q_x^{YOB} = q_x^{(base)} \cdot e^{-(YOB+x-baseYear)\cdot \lambda_x}$$
+ * Cohort life table approximation using age shift
+: Class `mortalityTable.ageShift`
+: Death probabilities for cohort $YOB$ are obtained by using death probabilities
+for cohort $X$ and modifying the technical age with a birth-year dependent shift:
+ $$q_x^{YOB} = q_{x+shift(YOB)}^{(base)}$$
+ <!-- * Observed life table -->
+ <!-- : Class `mortalityTable.observed` -->
+ <!-- : Death probabilities observed during several years. The probabilities are -->
+ <!-- stored as a matrix with observation year and age as dimensions. -->
+ * Mixed life table
+: Class `mortalityTable.mixed`
+: Arithmetic mean of two life tables with given weights. This approach is
+often used to generate unisex life tables by mixing male and female
+mortalities with given weights (e.g. 70:30 or 40:60)
+* Cohort life table using age-specific improvement factors
+: Class `mortalityTable.improvementFactors`
+: Project base life table using age-specific improvement factors.
+* Pension table
+: Class `pensionTable`
+: Four states: active, early retirement / invalidity, old-age pension, death (with optional widow)
+: All slots describe the corresponding transition probabilities by a
+: `mortalityTable`-derived object.
+
+## Loading the MortalityTables package
+```{R loading}
+library("MortalityTables")
+```
+
+## Provided Data Sets
+
+The package provides several real-life life tables published by census bureaus
+and actuarial associations around the world. You can use the function
+`mortalityTables.list` to list all available datasets (if no argument is given)
+or all datasets that match the given pattern (wildcard character is *). You can
+then use `mortalityTables.load` to load either one single data set or all
+datasets that match the pattern.
+
+```{r ListLoadTables}
+# list all datasets for Austria
+mortalityTables.list("Austria_*")
+
+# Load the German annuity table DAV 2004-R
+mortalityTables.load("Germany_Annuities_DAV2004R")
+
+# Load all Austrian data sets
+mortalityTables.load("Austria_*")
+```
+
+## Cohort and Period Mortality Data
+
+Cohort mortality vectors (for a given birth year) or period death probabilities (for a given observation year) can be extracted with the functions `periodDeathProbabilities()` and `deathProbabilities()`:
+
+```{r deathProbabilities}
+mortalityTables.load("Austria_Annuities")
+deathProbabilities(AVOe2005R.male, YOB = 1977, ages = 35:50)
+deathProbabilities(AVOe2005R.male, YOB = 2023, ages = 35:50)
+
+periodDeathProbabilities(AVOe2005R.male, Period = 2023, ages = 35:50)
+```
+
+If the mortality table is a cohort table, the trend is used to calculate the death probabilities for the given cohort or calendar year. If the table is a static life table, the period and cohort life tables will be identical. If the table is an observed table (i.e. observed death probabilities for each age and year), the data is extracted from the matrix' rows/columns or diagonals. In all cases, the user does not have use different methods for different underlying tables.
+
+## Plotting and Comparing Mortality Data
+
+There are two plotting functions using ggplot: `plotMortalityTables()` and `plotMortalityTableComparisons()` to plot the absolute and relative mortalities. For absolute mortalities, the `q(x)` axis employs a log10-scale. The returned plot is a normal ggplot2 object, so all features provided by ggplot2 can be adde to the plots.
+
+```{r Plotting, fig.width=8.5, fig.height=5}
+mortalityTables.load("Austria_Annuities")
+plotMortalityTables(AVOe2005R.male, AVOe2005R.male.unloaded, AVOe1996R.male, EROM.G1950.male,
+ YOB = 1977, ages = 0:99, legend.position = c(0.5, 0.65))
+plotMortalityTableComparisons(AVOe2005R.male, AVOe2005R.male.unloaded, AVOe1996R.male, EROM.G1950.male,
+ YOB = 1977, ages = 0:99, legend.position = c(0.5, 0.65))
+plotMortalityTrend(AVOe2005R.male, AVOe2005R.male.unloaded, AVOe1996R.male, AVOe1996R.male, EROM.G1950.male)
+```
+
+## Further information
+For further information on how to use the package, see the ["Using the MortalityTables Package"](https://cran.r-project.org/package=MortalityTables/vignettes/using-the-mortalityTables-package.html) vignette.
+
diff --git a/README.md b/README.md
index 4441faa..f16573e 100644
--- a/README.md
+++ b/README.md
@@ -1,109 +1,200 @@
+
+<!-- README.md is generated from README.Rmd. Please edit that file -->
+
# MortalityTables
-## Author: Reinhold Kainhofer, reinhold@kainhofer.com
-R package implementing actuarial mortality tables (period and cohort life tables)
+<!-- badges: start -->
+<!-- badges: end -->
+
+The goal of MortalityTables is to provide generic base classes and
+functions to handle all kinds of actuarial actuarial mortality tables
+(period and cohort life tables). Cohort and static life tables are
+implemented, observed data can be used, and existing life tables can be
+blended or extrapolated to derive new tables.
+
+Furthermore, plotting functions are provided for reports and
+publications.
+
+## Installation
+
+You can install the development version of MortalityTables from
+[GitHub](https://github.com/) with:
+
+``` r
+# install.packages("devtools")
+devtools::install_github("kainhofer/MortalityTables")
+```
## About the package
The MortalityTables package provides the `mortalityTable` base class and
-some derived classes to handle different types of mortality tables (also
-called life tables), mainly
-used for life insurance. Additionally it provides a plot function to compare
-multiple life tables either directly using the absolute mortalities in
-log-linear plots or using relative mortalities as percentages of a given
-reference table.
+some derived classes to handle different types of mortality tables (also
+called life tables), mainly used for life insurance. Additionally it
+provides a plot function to compare multiple life tables either directly
+using the absolute mortalities in log-linear plots or using relative
+mortalities as percentages of a given reference table.
### Types of Life Tables
Provided types of mortality tables are:
-* Base class
- : Class `mortalityTable`
-* Period life table
- : Class `mortalityTable.period(ages, deathProbs, ..., baseYear=2000)`
- : Death probabilities observed / predicted for one observation year;
- No dependency on the bith year is assumed.
-* Cohort life table using age-specific trends
- : Class `mortalityTable.trendProjection`
- : Death probabilities of a given base year are projected into the future
- using age-specific trends $\lambda_x$. The death probability of an $x$-year old in year
- `baseYear + n` is calculated as:
- $$q_x^{(baseYear+n)} = q_x^{(baseYear)} \cdot e^{-n\cdot\lambda_x}$$
- : Consequently, the death probabilities for a person born in year `YOB` can be calculated as
- $$q_x^{YOB} = q_x^{(base)} \cdot e^{-(YOB+x-baseYear)\cdot \lambda_x}$$
-* Cohort life table approximation using age shift
- : Class `mortalityTable.ageShift`
- : Death probabilities for cohort $YOB$ are obtained by using death probabilities
- for cohort $X$ and modifying the technical age with a birth-year dependent shift:
- $$q_x^{YOB} = q_{x+shift(YOB)}^{(base)}$$
-<!-- * Observed life table -->
-<!-- : Class `mortalityTable.observed` -->
-<!-- : Death probabilities observed during several years. The probabilities are -->
-<!-- stored as a matrix with observation year and age as dimensions. -->
-* Mixed life table
- : Class `mortalityTable.mixed`
- : Arithmetic mean of two life tables with given weights. This approach is
- often used to generate unisex life tables by mixing male and female
- mortalities with given weights (e.g. 70:30 or 40:60)
-* Cohort life table using age-specific improvement factors
- : Class `mortalityTable.improvementFactors`
- : Project base life table using age-specific improvement factors.
-* Pension table
- : Class `pensionTable`
- : Four states: active, early retirement / invalidity, old-age pension, death (with optional widow)
- : All slots describe the corresponding transition probabilities by a
- : `mortalityTable`-derived object.
+- Base class
+ Class `mortalityTable`
+
+- Period life table
+ Class `mortalityTable.period(ages, deathProbs, ..., baseYear=2000)`
+
+ Death probabilities observed / predicted for one observation year;
+ No dependency on the bith year is assumed.
+
+- Cohort life table using age-specific trends
+ Class `mortalityTable.trendProjection`
+
+ Death probabilities of a given base year are projected into the
+ future using age-specific trends $\lambda_x$. The death probability
+ of an $x$-year old in year `baseYear + n` is calculated as:
+ $$q_x^{(baseYear+n)} = q_x^{(baseYear)} \cdot e^{-n\cdot\lambda_x}$$
+
+ Consequently, the death probabilities for a person born in year
+ `YOB` can be calculated as
+ $$q_x^{YOB} = q_x^{(base)} \cdot e^{-(YOB+x-baseYear)\cdot \lambda_x}$$
+
+ - Cohort life table approximation using age shift
+
+ Class `mortalityTable.ageShift`
+
+ Death probabilities for cohort $YOB$ are obtained by using death
+ probabilities for cohort $X$ and modifying the technical age with a
+ birth-year dependent shift:
+ $$q_x^{YOB} = q_{x+shift(YOB)}^{(base)}$$
+ <!-- * Observed life table -->
+ <!-- : Class `mortalityTable.observed` -->
+ <!-- : Death probabilities observed during several years. The probabilities are -->
+ <!-- stored as a matrix with observation year and age as dimensions. -->
+
+ - Mixed life table
+
+ Class `mortalityTable.mixed`
+
+ Arithmetic mean of two life tables with given weights. This approach
+ is often used to generate unisex life tables by mixing male and
+ female mortalities with given weights (e.g. 70:30 or 40:60)
+
+- Cohort life table using age-specific improvement factors
+ Class `mortalityTable.improvementFactors`
+
+ Project base life table using age-specific improvement factors.
+
+- Pension table
+ Class `pensionTable`
+
+ Four states: active, early retirement / invalidity, old-age pension,
+ death (with optional widow)
+
+ All slots describe the corresponding transition probabilities by a
+
+ `mortalityTable`-derived object.
## Loading the MortalityTables package
-```
+
+``` r
library("MortalityTables")
```
## Provided Data Sets
-The package provides several real-life life tables published by census bureaus
-and actuarial associations around the world. You can use the function
-`mortalityTables.list` to list all available datasets (if no argument is given)
-or all datasets that match the given pattern (wildcard character is *). You can
-then use `mortalityTables.load` to load either one single data set or all
-datasets that match the pattern.
-
-```
-# list all available data sets
-mortalityTables.list()
+The package provides several real-life life tables published by census
+bureaus and actuarial associations around the world. You can use the
+function `mortalityTables.list` to list all available datasets (if no
+argument is given) or all datasets that match the given pattern
+(wildcard character is \*). You can then use `mortalityTables.load` to
+load either one single data set or all datasets that match the pattern.
+``` r
# list all datasets for Austria
mortalityTables.list("Austria_*")
+#> [1] "Austria_Annuities" "Austria_Annuities_AVOe1996R"
+#> [3] "Austria_Annuities_AVOe2005R" "Austria_Annuities_EROMF"
+#> [5] "Austria_Annuities_RR67" "Austria_Census"
+#> [7] "Austria_Endowments_ADSt2426_2Lives" "Austria_PopulationForecast"
+#> [9] "Austria_PopulationMCMC" "Austria_PopulationObserved"
+#> [11] "Austria_VUGesamtbestand_2012-16"
# Load the German annuity table DAV 2004-R
mortalityTables.load("Germany_Annuities_DAV2004R")
# Load all Austrian data sets
mortalityTables.load("Austria_*")
+#> Lade nötiges Paket: MortalityLaws
+#> Warning: Paket 'MortalityLaws' wurde unter R Version 4.2.3 erstellt
+```
+
+## Cohort and Period Mortality Data
+
+Cohort mortality vectors (for a given birth year) or period death
+probabilities (for a given observation year) can be extracted with the
+functions `periodDeathProbabilities()` and `deathProbabilities()`:
+
+``` r
+mortalityTables.load("Austria_Annuities")
+deathProbabilities(AVOe2005R.male, YOB = 1977, ages = 35:50)
+#> [1] 0.0006467352 0.0006741228 0.0007202125 0.0007820113 0.0008524437
+#> [6] 0.0009260103 0.0009794564 0.0010272832 0.0010731228 0.0011227093
+#> [11] 0.0011784509 0.0012409740 0.0013080864 0.0013817843 0.0014633494
+#> [16] 0.0015513107
+deathProbabilities(AVOe2005R.male, YOB = 2023, ages = 35:50)
+#> [1] 0.0001941029 0.0002041420 0.0002200821 0.0002411616 0.0002653197
+#> [6] 0.0002909132 0.0003106056 0.0003288675 0.0003468281 0.0003663459
+#> [11] 0.0003882554 0.0004128296 0.0004394048 0.0004687102 0.0005012581
+#> [16] 0.0005366270
+
+periodDeathProbabilities(AVOe2005R.male, Period = 2023, ages = 35:50)
+#> [1] 0.0004718782 0.0005066172 0.0005573996 0.0006231746 0.0006993210
+#> [6] 0.0007819197 0.0008511112 0.0009184673 0.0009869854 0.0010620137
+#> [11] 0.0011462722 0.0012409740 0.0013445246 0.0014595263 0.0015880515
+#> [16] 0.0017292761
+```
+
+If the mortality table is a cohort table, the trend is used to calculate
+the death probabilities for the given cohort or calendar year. If the
+table is a static life table, the period and cohort life tables will be
+identical. If the table is an observed table (i.e. observed death
+probabilities for each age and year), the data is extracted from the
+matrix’ rows/columns or diagonals. In all cases, the user does not have
+use different methods for different underlying tables.
+
+## Plotting and Comparing Mortality Data
+
+There are two plotting functions using ggplot: `plotMortalityTables()`
+and `plotMortalityTableComparisons()` to plot the absolute and relative
+mortalities. For absolute mortalities, the `q(x)` axis employs a
+log10-scale. The returned plot is a normal ggplot2 object, so all
+features provided by ggplot2 can be adde to the plots.
+
+``` r
+mortalityTables.load("Austria_Annuities")
+plotMortalityTables(AVOe2005R.male, AVOe2005R.male.unloaded, AVOe1996R.male, EROM.G1950.male,
+ YOB = 1977, ages = 0:99, legend.position = c(0.5, 0.65))
+```
+
+<img src="man/figures/README-Plotting-1.png" width="100%" />
+
+``` r
+plotMortalityTableComparisons(AVOe2005R.male, AVOe2005R.male.unloaded, AVOe1996R.male, EROM.G1950.male,
+ YOB = 1977, ages = 0:99, legend.position = c(0.5, 0.65))
```
+<img src="man/figures/README-Plotting-2.png" width="100%" />
+
+``` r
+plotMortalityTrend(AVOe2005R.male, AVOe2005R.male.unloaded, AVOe1996R.male, AVOe1996R.male, EROM.G1950.male)
+```
+
+<img src="man/figures/README-Plotting-3.png" width="100%" />
+
## Further information
-For further information on how to use the package, see the "Using the MortalityTables Package" vignette.
-
-## Changelog
-
-* Version 1.0 (30.3.2018):
- * Initial Submission to CRAN
-* Version 2.0 (27.8.2020):
- * Add various convenience functions to derive tables from data
- * implement dimensional information
- * extend plotting capabilities (more flexible)
- * Add more international tables / datasets
-* Version 2.0.1 (4.9.2020):
- * Fix performance issues with mortalityTables.list and mortalityTables.load
-* Version 2.0.2 (12.12.2020):
- * Add/fix some sample tables
- * gracefully handle missing suggested packages
- * First version of vignette about international tables
-* Version 2.0.3 (24.8.2021):
- * Fix vignette builds
-* Version 2.0.4 (19.10.2023):
- * Add new Austrian population mortality tables (2020/22)
-* Version 2.0.5 (27.10.2023):
- * Fix incorrect ages in Austrian population mortality
+For further information on how to use the package, see the [“Using the
+MortalityTables
+Package”](https://cran.r-project.org/package=MortalityTables/vignettes/using-the-mortalityTables-package.html)
+vignette.
diff --git a/man/MortalityTables-package.Rd b/man/MortalityTables-package.Rd
index bc1481a..e25fe14 100644
--- a/man/MortalityTables-package.Rd
+++ b/man/MortalityTables-package.Rd
@@ -6,7 +6,7 @@
\alias{MortalityTables-package}
\title{Provide life table classes for life insurance purposes}
\description{
-Classes to implement and plot cohort life tables for actuarial calculations. In particular, birth-year dependent mortality tables using a yearly trend to extrapolate from a base year are implemented, as well as period life table, cohort life tables using an age shift, and merged life tables.
+Classes to implement, analyze and plot cohort life tables for actuarial calculations. Birth-year dependent cohort mortality tables using a yearly trend to extrapolate from a base year are implemented, as well as period life table, cohort life tables using an age shift, and merged life tables. Additionally, several data sets from various countries are included to provide widely-used tables out of the box.
}
\seealso{
Useful links:
@@ -17,6 +17,6 @@ Useful links:
}
\author{
-\strong{Maintainer}: Reinhold Kainhofer \email{reinhold@kainhofer.com}
+\strong{Maintainer}: Reinhold Kainhofer \email{reinhold@kainhofer.com} [copyright holder]
}
diff --git a/man/figures/README-Plotting-1.png b/man/figures/README-Plotting-1.png
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A#Q*>R
literal 0
HcmV?d00001
--
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