V2.0.2: Gracefully handle missing suggested packages

Conditionally call functions from suggested / enhanced packages.
In the vignette, print a warning and disable all evaluation if a suggested package is missing that is needed for the vignette.

.Renviron

+_R_CHECK_DEPENDS_ONLY_=true

DESCRIPTION

 Package: MortalityTables
 Type: Package
-Version: 2.0.1
-Date: 2020-09-07
+Version: 2.0.2
+Date: 2020-12-12
 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]
@@ -11,15 +11,16 @@ BugReports: https://gitlab.open-tools.net/R/r-mortality-tables/-/issues
 Encoding: UTF-8
 Depends:
     ggplot2,
-    R (>= 2.10)
+    R (>= 3.5)
 Imports:
     methods,
     scales,
     utils,
     pracma
-Suggests:
-    lifecontingencies,
+Enhances:
     MortalityLaws,
+    lifecontingencies
+Suggests:
     knitr,
     tidyverse,
     rmarkdown,

R/ages.R

@@ -7,9 +7,11 @@ NULL
 #' @param ... Currently unused
 #'
 #' @examples
-#' mortalityTables.load("Austria_*")
+#' mortalityTables.load("Austria_Annuities")
 #' ages(AVOe2005R.male)
 #' ages(AVOe1996R.male)
+#'
+#' mortalityTables.load("Austria_Census")
 #' ages(mort.AT.census.2011.male)
 #'
 #' @exportMethod ages

R/lifeTable.R

@@ -8,12 +8,13 @@ NULL
 #'            of the life table
 #'
 #' @examples
+#' if (requireNamespace("lifecontingencies", quietly = TRUE)) {
 #' library("lifecontingencies")
 #' mortalityTables.load("Austria_Annuities")
 #' lifeTable(AVOe2005R.male, YOB = 2017)
 #' axn(lifeTable(AVOe2005R.male, YOB = 1975), x = 65, i = 0.03)
 #' axn(lifeTable(AVOe2005R.male, YOB = 2017), x = 65, i = 0.03)
-#'
+#' }
 #' @exportMethod lifeTable
 setGeneric("lifeTable", function(object, ...) standardGeneric("lifeTable"));
 
@@ -25,5 +26,29 @@ setMethod("lifeTable","mortalityTable",
               if (qx[[length(qx)]] != 1) {
                   qx = c(qx, 1, 1);
               }
-              lifecontingencies::probs2lifetable(qx, type = "qx")
+              if (requireNamespace("lifecontingencies", quietly = TRUE)) {
+                  lifecontingencies::probs2lifetable(qx, type = "qx")
+              } else {
+                  warning("The MortalityTables::lifeTable function requires the lifecontingencies package to be installed. Please install it, if you intend to use the lifeTable function.")
+              }
+          })
+
+#' @describeIn lifeTable Return the lifetable object (package lifecontingencies) from the mortalityTable objects stored in the array
+setMethod("lifeTable", "array",
+          function(object,  ...) {
+              array(
+                  lapply(object, lifeTable,  ...),
+                  dim = dim(object), dimnames = dimnames(object))
           })
+#' @describeIn lifeTable Return the lifetable object (package lifecontingencies)  from the mortalityTable objects stored in the list
+setMethod("lifeTable", "list",
+          function(object,  ...) {
+              lapply(object, lifeTable, ...)
+          })
+
+#' @describeIn lifeTable Empty dummy function to handle unassigned variables
+setMethod("lifeTable", "NULL",
+          function(object,  ...) {
+              NULL
+          })
+

R/utilityFunctions.R

@@ -436,7 +436,11 @@ mT.fitExtrapolationLaw = function(table, method = "LF2", law = "HP",
                                   fit = 75:99, extrapolate = 80:120,
                                   fadeIn = 80:90, fadeOut = NULL, raw = NULL) {
     if (!is(table, "mortalityTable"))
-        stop("First argument must be a mortalityTable.")
+        stop("mT.fitExtrapolationLaw: First argument must be a mortalityTable.")
+    if (!requireNamespace("MortalityLaws", quietly = TRUE)) {
+        warning("mT.fitExtrapolationLaw: The package `MortalityLaws` is required for this function. Please install it to be able to use mT.fitExtrapolationLaw. Unmodified table will be returned.")
+        return(table)
+    }
     ages = ages(table)
     # if (!is.null(table@exposures) && !is.na(table@exposures)) {
         # Ex = table@exposures

README.md

@@ -84,3 +84,15 @@ mortalityTables.load("Austria_*")
 
 ## 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
+* 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

man/ages.Rd

@@ -39,9 +39,11 @@ Return the defined ages of the life table
 }}
 
 \examples{
-mortalityTables.load("Austria_*")
+mortalityTables.load("Austria_Annuities")
 ages(AVOe2005R.male)
 ages(AVOe1996R.male)
+
+mortalityTables.load("Austria_Census")
 ages(mort.AT.census.2011.male)
 
 }

man/lifeTable.Rd

@@ -3,11 +3,20 @@
 \name{lifeTable}
 \alias{lifeTable}
 \alias{lifeTable,mortalityTable-method}
+\alias{lifeTable,array-method}
+\alias{lifeTable,list-method}
+\alias{lifeTable,NULL-method}
 \title{Return the lifetable object (package lifecontingencies) for the cohort life table}
 \usage{
 lifeTable(object, ...)
 
 \S4method{lifeTable}{mortalityTable}(object, ...)
+
+\S4method{lifeTable}{array}(object, ...)
+
+\S4method{lifeTable}{list}(object, ...)
+
+\S4method{lifeTable}{`NULL`}(object, ...)
 }
 \arguments{
 \item{object}{The life table object (class inherited from mortalityTable)}
@@ -22,13 +31,20 @@ Return the lifetable object (package lifecontingencies) for the cohort life tabl
 \itemize{
 \item \code{mortalityTable}: Return the lifetable object (package lifecontingencies)
 for the cohort life table
+
+\item \code{array}: Return the lifetable object (package lifecontingencies) from the mortalityTable objects stored in the array
+
+\item \code{list}: Return the lifetable object (package lifecontingencies)  from the mortalityTable objects stored in the list
+
+\item \code{NULL}: Empty dummy function to handle unassigned variables
 }}
 
 \examples{
+if (requireNamespace("lifecontingencies", quietly = TRUE)) {
 library("lifecontingencies")
 mortalityTables.load("Austria_Annuities")
 lifeTable(AVOe2005R.male, YOB = 2017)
 axn(lifeTable(AVOe2005R.male, YOB = 1975), x = 65, i = 0.03)
 axn(lifeTable(AVOe2005R.male, YOB = 2017), x = 65, i = 0.03)
-
+}
 }

vignettes/international-mortality-tables-overview.Rmd

@@ -21,8 +21,19 @@ knitr::opts_chunk$set(
 )
 ```
 
+```{r PackageCheck, echo = FALSE}
+required <- c("tidyverse")
+if (!all(sapply(required, 
+                function(pkg) requireNamespace(pkg, quietly = TRUE)))) {
+  message(paste("This vignette needs the followig packages:\n\t", 
+                paste(required, collapse = " "), 
+                "\nSince not all are installed, code will not be executed: "))
+  knitr::opts_chunk$set(eval = FALSE)
+}
+```
+
 ```{r setup}
-library(magrittr)
+library(tidyverse, quietly = TRUE)
 library(MortalityTables)
 mortalityTables.load("Austria_Census")
 ```
@@ -49,6 +60,7 @@ Annuity tables in Austria are traditionally published by the [Actuarial Associat
 ### ÖVM 59/61 - RR 67
 
 [TODO: Get actual table data and publication]
+
 * Source: H. Nabl: ÖVM 59/61 - RR67 - 3%, Die Versicherungsrundschau, 22. Jahrgang, Heft 12, Dez. 1967, p.373--380.
 
 ```{r}
@@ -402,7 +414,6 @@ PKBestandstafel.2010.16
 ```{r PKBestand.vergleich}
 plotMortalityTables(PKBestandstafel.2010.16[,,"qx", "raw"], legend.position = "right", title = "Austrian pension fund mortalities 2010-16", aes = aes(color = type)) +
   facet_grid(sex ~ .) + labs(color = "Collective")
-PKBestandstafel.2010.16[1,1,1,1]
 ```
 
 
@@ -664,6 +675,7 @@ Fischer Verlag, Weissenburg/Bayern, 1959
 [TODO]
 
 https://aktuar.de/unsere-themen/lebensversicherung/Seiten/default.aspx
+
 * Source: Klaus Heubeck, Richard Herrmann und Gabriele D’Souza. „Die Richttafeln 2005 G – Modell, Herleitung, Formeln“. In: Blätter der DGVFM 27.3 (Apr. 2006), S. 473–517.
 
 
@@ -701,6 +713,7 @@ Source: [https://content.naic.org/sites/default/files/pbr_data_valuation_manual_
 
 Source: Society of Actuaries. RP-2014 Mortality Tables Report. Techn. Ber. Okt. 2014. URL: https://www.soa.
 org/experience-studies/2014/research-2014-rp/.
+
 Source: Society of Actuaries. Mortality Improvement Scale MP-2014 Report. Techn. Ber. Okt. 2014. URL: https:
 //www.soa.org/experience-studies/2014/research-2014-mp/.
 

vignettes/using-the-mortalityTables-package.R

-## ----echo = FALSE-------------------------------------------------------------
-knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
-options(tidyverse.quiet = TRUE)
-
-## ----message=FALSE------------------------------------------------------------
-library("MortalityTables")
-
-## -----------------------------------------------------------------------------
-# list all available data sets
-mortalityTables.list()
-
-# list all datasets for Austria
-mortalityTables.list("Austria_*")
-
-# Load the German annuity table DAV 2004-R
-mortalityTables.load("Germany_Annuities_DAV2004R")
-
-# Load all Austrian annuity data sets
-mortalityTables.load("Austria_Annuities*")
-mortalityTables.load("Austria_Census")
-
-## -----------------------------------------------------------------------------
-# Log-linear plot comparing some Austrian census tables
-plot(mort.AT.census.1951.male, mort.AT.census.1991.male, 
-     mort.AT.census.2001.male, mort.AT.census.2011.male, 
-     legend.position = c(1,0))
-
-# Relative death probabilities in percentage of the latest census
-plot(mort.AT.census.1951.male, mort.AT.census.1991.male, 
-     mort.AT.census.2001.male, 
-     reference = mort.AT.census.2011.male, legend.position = c(1,0.75), ylim = c(0,4))
-
-## -----------------------------------------------------------------------------
-# Comparison of two Austrian annuity tables for birth year 1977
-plot(AVOe1996R.male, AVOe2005R.male, YOB = 1977, title = "Comparison for YOB=1977")
-
-# Comparison of two Austrian annuity tables for observation year 2020
-plot(AVOe1996R.male, AVOe2005R.male, Period = 2020, title = "Comparison for observation year 2020")
-
-
-## ----message=FALSE------------------------------------------------------------
-mortalityTables.load("Austria_Annuities")
-# Get the cohort death probabilities for Austrian Annuitants born in 1977:
-qx.coh1977 = deathProbabilities(AVOe2005R.male, YOB = 1977)
-
-# Get the period death probabilities for Austrian Annuitants observed in the year 2020:
-qx.per2020 = periodDeathProbabilities(AVOe2005R.male, Period = 2020)
-
-## -----------------------------------------------------------------------------
-# Get the cohort death probabilities for Austrian Annuitants born in 1977 as a mortalityTable.period object:
-table.coh1977 = getCohortTable(AVOe2005R.male, YOB = 1977)
-
-# Get the period death probabilities for Austrian Annuitants observed in the year 2020:
-table.per2020 = getPeriodTable(AVOe2005R.male, Period = 2020)
-
-# Compare those two in a plot:
-plot(table.coh1977, table.per2020, title = "Comparison of cohort 1977 with Period 2020", legend.position = c(1,0))
-
-
-## ----DimensionalInfoPlot------------------------------------------------------
-plotMortalityTables(
-  mort.AT.census[c("m", "w"), c("1951", "1991", "2001", "2011")]) + 
-  aes(color = as.factor(year), linetype = sex) + labs(color = "Period", linetype = "Sex")
-
-## ----DimensionalInformationStorage--------------------------------------------
-mort.AT.census.2011.male@data$dim
-
-## -----------------------------------------------------------------------------
-lt = mortalityTable.period(name = "Sample period lifetable", ages = 1:99, deathProbs = exp(-(99:1)/10))
-plot(lt, title = "Simple log-linear period mortality table")
-deathProbabilities(lt)
-
-
-## -----------------------------------------------------------------------------
-atPlus2 = mortalityTable.trendProjection(
-    name = "Austrian Census Males 2011, 2% yearly trend",
-    baseYear = 2011,
-    deathProbs = deathProbabilities(mort.AT.census.2011.male),
-    ages = ages(mort.AT.census.2011.male),
-    trend = rep(0.02, length(ages(mort.AT.census.2011.male)))
-)
-
-## -----------------------------------------------------------------------------
-atPlus2.damp = mortalityTable.trendProjection(
-    name = "Austrian M '11, 2% yearly, damping until 2111",
-    baseYear = 2011,
-    deathProbs = deathProbabilities(mort.AT.census.2011.male),
-    ages = ages(mort.AT.census.2011.male),
-    trend = rep(0.02, length(ages(mort.AT.census.2011.male))),
-    # damping function: 2011: full effect, linear reduction until yearly trend=0 in 2111:
-    # 2011: 100%, 2012: 99%, 2013: 98% => For 2013 we have a cumulative trend 
-    # of 297% instead of 300% for three full yearly trends!
-    dampingFunction = function(n) { n - n * (n + 1) / 2 / 100 }
-)
-
-plot(mort.AT.census.2011.male, atPlus2, atPlus2.damp, YOB = 2011, legend.position = c(0.8,0.75))
-
-## -----------------------------------------------------------------------------
-atPlus2.damp2 = mortalityTable.trendProjection(
-    name = "Austrian M '11, 2% yearly, 1% long-term",
-    baseYear = 2011,
-    deathProbs = deathProbabilities(mort.AT.census.2011.male),
-    ages = ages(mort.AT.census.2011.male),
-    trend = rep(0.02, length(ages(mort.AT.census.2011.male))),
-    trend2 = rep(0.01, length(ages(mort.AT.census.2011.male))),
-    # damping function interpolates between the two trends: 
-    # until 2021 trend 1, from 2031 trend 2, linearly beteen
-    dampingFunction = function(year) { 
-        if (year <= 2021) 1
-        else if (year > 2031) 14.5/(year - 2011)
-        else 1 - (year - 2021)*(year - 2021 + 1) / 20 / (year - 2011)
-    }
-)
-
-plot(mort.AT.census.2011.male, atPlus2, atPlus2.damp, atPlus2.damp2, YOB = 2011, legend.position = c(0.02, 0.98), legend.justification = c(0, 1))
-
-## -----------------------------------------------------------------------------
-baseTableShift = getCohortTable(atPlus2, YOB = 2011);
-baseTableShift@name = "Base table of the shift (YOB 2011)"
-
-atShifted = mortalityTable.ageShift(
-    name = "Approximation with age shift",
-    baseYear = 2011,
-    deathProbs = deathProbabilities(baseTableShift),
-    ages = ages(baseTableShift),
-    ageShifts = data.frame(
-        shifts = c(
-            rep( 0, 3), 
-            rep(-1, 3), 
-            rep(-2, 3), 
-            rep(-3, 3), 
-            rep(-4, 3), 
-            rep(-5, 3), 
-            rep(-6, 3)
-        ),
-        row.names = 2011:2031
-    )
-)
-
-ageShift(atShifted, YOB = 2021)
-
-plot(baseTableShift, atPlus2, atShifted, YOB = 2021, legend.position = c(0.8,0.75))
-
-## -----------------------------------------------------------------------------
-b = AVOe2005R.female 
-b@name = "Modified Copy"
-# only b is modified, not the original table
-b@modification = function(qx) pmax(qx, 0.01)  
-plot(AVOe2005R.female, b, YOB = 2000)
-
-## -----------------------------------------------------------------------------
-AVOe2005R.female.sec = setLoading(AVOe2005R.female, loading = 0.1);
-# Make sure the modified table has a new name, otherwise plots might break
-AVOe2005R.female.sec@name = "Table with 10% loading"
-plot(AVOe2005R.female, AVOe2005R.female.sec, title = "Original and modified table")
-
-## -----------------------------------------------------------------------------
-AVOe2005R.female.mod = setModification(AVOe2005R.female, modification = function(qx) pmax(0.03, qx));
-# Make sure the modified table has a new name, otherwise plots might break
-AVOe2005R.female.mod@name = "Modified table (lower bound of 3%)"
-plot(AVOe2005R.female, AVOe2005R.female.mod, title = "Original and modified table")
-
-## ----AustrianPopulation.RawData-----------------------------------------------
-library(tidyverse)
-data("PopulationData.AT2017", package = "MortalityTables")
-PopulationData.AT2017.raw = PopulationData.AT2017 %>%
-  select(age, exposure.total, deaths.total) %>%
-  mutate(qraw = deaths.total / (exposure.total + deaths.total/2))
-
-## ----AustrianPopulationTableRaw-----------------------------------------------
-PopulationTable.AT2017 = mortalityTable.period(
-  name = "Austrian Population Mortality 2017 (raw)", 
-  baseYear = 2017,
-  deathProbs = PopulationData.AT2017.raw$qraw,
-  ages = PopulationData.AT2017.raw$age,
-  exposures = PopulationData.AT2017.raw$exposure.total,
-  data = list(
-    deaths = PopulationData.AT2017.raw$deaths.total,
-    dim = list(sex = "u", collar = "Population", type = "raw", year = "2017")
-  )
-)
-plotMortalityTables(PopulationTable.AT2017, title = "Austrian population mortality (raw), 2017")
-
-## ----AustrianPopulationTableSmooth--------------------------------------------
-PopulationTable.AT2017.smooth = PopulationTable.AT2017 %>%
-  whittaker.mortalityTable(lambda = 1/10, d = 2, name.postfix = ", Whittaker") %>%
-  mT.setDimInfo(type = "smoothed")
-plotMortalityTables(PopulationTable.AT2017, PopulationTable.AT2017.smooth, title = "Austrian population mortality (raw and smoothed), 2017")  +
-  aes(colour = type)
-
-## ----AustrianPopulationTableCut100--------------------------------------------
-PopulationData.AT2017.raw %>% filter(age > 90)
-PopulationTable.AT2017.cut = PopulationTable.AT2017.smooth %>%
-  mT.fillAges(0:99) %>%
-  mT.setName("Austrian Population Mortality 2017, Whittaker-smoothed and cut at age 99")
-
-## ----AustrianPopulationTableExtrapolated--------------------------------------
-PopulationTable.AT2017.ex = PopulationTable.AT2017.smooth %>%
-  mT.fitExtrapolationLaw(law = "HP2", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
-  mT.setDimInfo(type = "smoothed and extrapolated")
-plotMortalityTables(PopulationTable.AT2017, PopulationTable.AT2017.smooth, PopulationTable.AT2017.ex, title = "Austrian population mortality (raw and smoothed), 2017")  +
-  aes(colour = type)
-
-## ----AustrianPopulationTableFitComparison-------------------------------------
-plotMortalityTables(
-  PopulationTable.AT2017, 
-  PopulationTable.AT2017.smooth %>%
-    mT.fitExtrapolationLaw(law = "HP2", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
-    mT.setDimInfo(type = "Extrapolation: HP2, Fit 75--99"),
-  
-  PopulationTable.AT2017.smooth %>%
-    mT.fitExtrapolationLaw(law = "HP2", fit = 75:85, extrapolate = 80:120, fadeIn = 80:95) %>%
-    mT.setDimInfo(type = "Extrapolation: HP, Fit 75--85"),
-  
-  PopulationTable.AT2017.smooth %>%
-    mT.fitExtrapolationLaw(law = "HP2", fit = 90:110, extrapolate = 80:120, fadeIn = 90:100) %>%
-    mT.setDimInfo(type = "Extrapolation: HP2, Fit 90--110"),
-  
-  title = "Examples of different fitting ranges for extrapolation")  +
-  aes(colour = type)
-
-## ----AustrianPopulationTableFitFunctionComparison-----------------------------
-plotMortalityTables(
-  PopulationTable.AT2017, 
-  PopulationTable.AT2017.smooth %>%
-    mT.fitExtrapolationLaw(law = "HP2", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
-    mT.setDimInfo(type = "HP2"),
-  PopulationTable.AT2017.smooth %>%
-    mT.fitExtrapolationLaw(law = "thiele", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
-    mT.setDimInfo(type = "thiele"),
-  PopulationTable.AT2017.smooth %>%
-    mT.fitExtrapolationLaw(law = "ggompertz", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
-    mT.setDimInfo(type = "ggompertz"),
-  PopulationTable.AT2017.smooth %>%
-    mT.fitExtrapolationLaw(law = "carriere1", fit = 75:99, extrapolate = 80:120, fadeIn = 80:95) %>%
-    mT.setDimInfo(type = "carriere1"),
-
-  title = "Examples of different fitting functions for extrapolation (fit 75--99)", 
-  ages = 75:120, legend.position = "bottom", legend.key.width = unit(15, "mm"))  +
-  aes(colour = type) + labs(colour = "Mortality Law")
-
-## ----AustrianPopulationTableTrendForecast-------------------------------------
-mortalityTables.load("Austria_PopulationForecast")
-plotMortalityTrend(mort.AT.forecast, title = "Forecast trend (medium scenario) by Statistik Austria")
-
-## ----AustrianPopulationTableTrend---------------------------------------------
-PopulationTable.AT2017.trend = PopulationTable.AT2017.ex %>%
-  mT.addTrend(mort.AT.forecast$m@trend, trendages = ages(mort.AT.forecast$m)) %>%
-  mT.setDimInfo(type = "smoothed, extrapolated, trend")
-
-PopulationTable.AT2017.trend.ex = PopulationTable.AT2017.trend %>%
-  mT.extrapolateTrendExp(95) %>%
-  mT.setDimInfo(type = "smoothed, extrapolated, trend extrapolated")
-
-plotMortalityTrend(PopulationTable.AT2017.trend, PopulationTable.AT2017.trend.ex,
-                   title = "Extrapolating the trend via Exponential function") +
-  aes(color = type)
-
-
-
-plotMortalityTables(PopulationTable.AT2017, PopulationTable.AT2017.smooth, PopulationTable.AT2017.ex, PopulationTable.AT2017.trend.ex, YOB = 1980, title = "Austrian population mortality (Period 2017 vs. Generation 1980)", legend.position = c(0.01, 0.99), legend.justification = c(0,1))  +
-  aes(colour = type)
-
-
-## ----AustrianPopulationTableFinal---------------------------------------------
-# Lots of non-essential or support information is stored inside the table's data field:
-PopulationTable.AT2017.trend.ex@data$whittaker
-
-# Clean up the table (remove all non-essential data, but do not modify results)
-PopulationTable.AT2017.Cohort.FINAL = PopulationTable.AT2017.trend.ex %>%
-  mT.cleanup() %>%
-  mT.round(digits = 6) %>%
-  mT.setName("Austrian Population Mortality, Period 2017 with trend projection")
-
-
-## ----AustrianPopulationTableScaled--------------------------------------------
-TableForProduct = PopulationTable.AT2017.Cohort.FINAL %>%
-  mT.scaleProbs(factor = 1.25, name.postfix = "10% security added")
-
-plotMortalityTables(TableForProduct, PopulationTable.AT2017.Cohort.FINAL, 
-                    title = "Adding a security loading of 25%", Period = 2017, legend.position = "bottom")
-

vignettes/using-the-mortalityTables-package.Rmd

@@ -15,6 +15,17 @@ vignette: >
   %\VignetteEncoding{UTF-8}
 ---
 
+```{r PackageCheck}
+required <- c("tidyverse")
+if (!all(sapply(required, 
+                function(pkg) requireNamespace(pkg, quietly = TRUE)))) {
+  message(paste("This vignette needs the followig packages:\n\t", 
+                paste(required, collapse = " "), 
+                "\nSince not all are installed, code will not be executed: "))
+  knitr::opts_chunk$set(eval = FALSE)
+}
+```
+
 ```{r echo = FALSE}
 knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
 options(tidyverse.quiet = TRUE)