...
 
Commits (4)
......@@ -5,3 +5,4 @@
R/Companies/
Formulas_Reference/2013*.xls*
inst/doc
desktop.ini
......@@ -23,9 +23,8 @@ Description: Classes to implement and plot cohort life tables
as well as period life table, cohort life tables using an age shift, and
merged life tables.
License: GPL (>= 2)
RoxygenNote: 6.0.1
Collate:
'mortalityTable.R'
RoxygenNote: 6.1.0.9000
Collate: 'mortalityTable.R'
'mortalityTable.period.R'
'mortalityTable.ageShift.R'
'ageShift.R'
......
......@@ -58,12 +58,14 @@ plotMortalityTables = function(
if (missing(xlab)) xlab = "Alter";
if (missing(ylab)) ylab = expression(paste("Sterbewahrscheinlichkeit ", q[x]));
data = subset(data, y > 0)
if (!is.null(ages)) {
data = data[data$x %in% ages,]
}
pl = ggplot(subset(data, y > 0), aes(x = x, y = y, color = group))
if (log) {
data = subset(data, y > 0)
}
pl = ggplot(data, aes(x = x, y = y, color = group))
if (!is.null(aes)) {
pl = pl + aes
}
......
Census-Mortality Tables Austrian Unisex
Source: Statistik Austria. Alexander Hanika
x;1868/71;1879/82;1889/92;1899/1902;1909/12;1930/33;1949/51;1959/61;1970/72;1980/82;1990/92;2000/02;2010/12
0;;;;;;;;;;;;;0.003562
1;;;;;;;;;;;;;0.000231
2;;;;;;;;;;;;;0.000184
3;;;;;;;;;;;;;0.000143
4;;;;;;;;;;;;;0.000110
5;;;;;;;;;;;;;0.000086
6;;;;;;;;;;;;;0.000073
7;;;;;;;;;;;;;0.000069
8;;;;;;;;;;;;;0.000070
9;;;;;;;;;;;;;0.000071
10;;;;;;;;;;;;;0.000073
11;;;;;;;;;;;;;0.000081
12;;;;;;;;;;;;;0.000096
13;;;;;;;;;;;;;0.000120
14;;;;;;;;;;;;;0.000158
15;;;;;;;;;;;;;0.000210
16;;;;;;;;;;;;;0.000272
17;;;;;;;;;;;;;0.000341
18;;;;;;;;;;;;;0.000410
19;;;;;;;;;;;;;0.000469
20;;;;;;;;;;;;;0.000509
21;;;;;;;;;;;;;0.000528
22;;;;;;;;;;;;;0.000525
23;;;;;;;;;;;;;0.000509
24;;;;;;;;;;;;;0.000492
25;;;;;;;;;;;;;0.000481
26;;;;;;;;;;;;;0.000474
27;;;;;;;;;;;;;0.000471
28;;;;;;;;;;;;;0.000470
29;;;;;;;;;;;;;0.000475
30;;;;;;;;;;;;;0.000486
31;;;;;;;;;;;;;0.000503
32;;;;;;;;;;;;;0.000526
33;;;;;;;;;;;;;0.000555
34;;;;;;;;;;;;;0.000591
35;;;;;;;;;;;;;0.000631
36;;;;;;;;;;;;;0.000675
37;;;;;;;;;;;;;0.000724
38;;;;;;;;;;;;;0.000782
39;;;;;;;;;;;;;0.000849
40;;;;;;;;;;;;;0.000931
41;;;;;;;;;;;;;0.001032
42;;;;;;;;;;;;;0.001152
43;;;;;;;;;;;;;0.001292
44;;;;;;;;;;;;;0.001452
45;;;;;;;;;;;;;0.001630
46;;;;;;;;;;;;;0.001828
47;;;;;;;;;;;;;0.002045
48;;;;;;;;;;;;;0.002283
49;;;;;;;;;;;;;0.002542
50;;;;;;;;;;;;;0.002823
51;;;;;;;;;;;;;0.003125
52;;;;;;;;;;;;;0.003455
53;;;;;;;;;;;;;0.003814
54;;;;;;;;;;;;;0.004208
55;;;;;;;;;;;;;0.004643
56;;;;;;;;;;;;;0.005129
57;;;;;;;;;;;;;0.005664
58;;;;;;;;;;;;;0.006246
59;;;;;;;;;;;;;0.006875
60;;;;;;;;;;;;;0.007543
61;;;;;;;;;;;;;0.008243
62;;;;;;;;;;;;;0.008957
63;;;;;;;;;;;;;0.009696
64;;;;;;;;;;;;;0.010449
65;;;;;;;;;;;;;0.011218
66;;;;;;;;;;;;;0.012009
67;;;;;;;;;;;;;0.012872
68;;;;;;;;;;;;;0.013840
69;;;;;;;;;;;;;0.014917
70;;;;;;;;;;;;;0.016150
71;;;;;;;;;;;;;0.017572
72;;;;;;;;;;;;;0.019231
73;;;;;;;;;;;;;0.021182
74;;;;;;;;;;;;;0.023447
75;;;;;;;;;;;;;0.026103
76;;;;;;;;;;;;;0.029200
77;;;;;;;;;;;;;0.032853
78;;;;;;;;;;;;;0.037141
79;;;;;;;;;;;;;0.042084
80;;;;;;;;;;;;;0.047756
81;;;;;;;;;;;;;0.054211
82;;;;;;;;;;;;;0.061523
83;;;;;;;;;;;;;0.069640
84;;;;;;;;;;;;;0.078587
85;;;;;;;;;;;;;0.088520
86;;;;;;;;;;;;;0.099541
87;;;;;;;;;;;;;0.112010
88;;;;;;;;;;;;;0.125804
89;;;;;;;;;;;;;0.140964
90;;;;;;;;;;;;;0.157392
91;;;;;;;;;;;;;0.175061
92;;;;;;;;;;;;;0.193823
93;;;;;;;;;;;;;0.213746
94;;;;;;;;;;;;;0.234421
95;;;;;;;;;;;;;0.256099
96;;;;;;;;;;;;;0.278709
97;;;;;;;;;;;;;0.301820
98;;;;;;;;;;;;;0.325508
99;;;;;;;;;;;;;0.349389
100;;;;;;;;;;;;;1.000000
101
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Statistik Austria: Bevölkerungsprognose 2014-2080 – Basistafel und jährlicher Trend,,,,
,,,,
,q Männer 2014,Männer,q Frauen 2014,Frauen
,q M 2014,M,q F 2014,F
0,0.00329510385037614,-0.0443394515333271,0.00281572638727908,-0.0461691934651078
1,0.000255226677421527,-0.0428143357006832,0.000162851795562211,-0.0444917353582905
2,0.000173567998795988,-0.0421435262403271,0.000132130160011204,-0.0431499486749107
......
......@@ -7,9 +7,10 @@ stopifnot(require(methods), require(utils), require(MortalityTables)) # Mortalit
a.vz.dataM = utils::read.csv(system.file("extdata", "Austria_Census_Male.csv", package = "MortalityTables"), skip = 3);
a.vz.dataF = utils::read.csv(system.file("extdata", "Austria_Census_Female.csv", package="MortalityTables"), skip = 3);
a.vz.dataF = utils::read.csv(system.file("extdata", "Austria_Census_Female.csv", package = "MortalityTables"), skip = 3);
a.vz.dataU = utils::read.csv(system.file("extdata", "Austria_Census_Unisex.csv", package = "MortalityTables"), skip = 3);
censtable = function(data, name, qslot, baseYear=1900, sex = "m") {
censtable = function(data, name, qslot, baseYear = 1900, sex = "m") {
qx = data[names(data) == qslot];
ix = complete.cases(qx);
mortalityTable.period(name = name, ages = data$x[ix], deathProbs = qx[ix,], baseYear = baseYear,
......@@ -19,39 +20,40 @@ censtable = function(data, name, qslot, baseYear=1900, sex = "m") {
)
}
mort.AT.census.1869.male = censtable(a.vz.dataM, name="ÖVSt 1868/71 M", baseYear=1869, qslot="X1868.71", sex = "m")
mort.AT.census.1880.male = censtable(a.vz.dataM, name="ÖVSt 1879/82 M", baseYear=1880, qslot="X1879.82", sex = "m")
mort.AT.census.1890.male = censtable(a.vz.dataM, name="ÖVSt 1889/92 M", baseYear=1890, qslot="X1889.92", sex = "m")
mort.AT.census.1900.male = censtable(a.vz.dataM, name="ÖVSt 1899/1902 M", baseYear=1900, qslot="X1899.1902", sex = "m")
mort.AT.census.1910.male = censtable(a.vz.dataM, name="ÖVSt 1909/12 M", baseYear=1910, qslot="X1909.12", sex = "m")
mort.AT.census.1931.male = censtable(a.vz.dataM, name="ÖVSt 1930/33 M", baseYear=1931, qslot="X1930.33", sex = "m")
mort.AT.census.1951.male = censtable(a.vz.dataM, name="ÖVSt 1949/51 M", baseYear=1951, qslot="X1949.51", sex = "m")
mort.AT.census.1961.male = censtable(a.vz.dataM, name="ÖVSt 1959/61 M", baseYear=1961, qslot="X1959.61", sex = "m")
mort.AT.census.1971.male = censtable(a.vz.dataM, name="ÖVSt 1970/72 M", baseYear=1971, qslot="X1970.72", sex = "m")
mort.AT.census.1981.male = censtable(a.vz.dataM, name="ÖVSt 1980/82 M", baseYear=1981, qslot="X1980.82", sex = "m")
mort.AT.census.1991.male = censtable(a.vz.dataM, name="ÖVSt 1990/92 M", baseYear=1991, qslot="X1990.92", sex = "m")
mort.AT.census.2001.male = censtable(a.vz.dataM, name="ÖVSt 2000/02 M", baseYear=2001, qslot="X2000.02", sex = "m")
mort.AT.census.2011.male = censtable(a.vz.dataM, name="ÖVSt 2010/2012 M", baseYear=2011, qslot="X2010.12", sex = "m")
mort.AT.census.1869.male = censtable(a.vz.dataM, name = "ÖVSt 1868/71 M", baseYear = 1869, qslot = "X1868.71", sex = "m")
mort.AT.census.1880.male = censtable(a.vz.dataM, name = "ÖVSt 1879/82 M", baseYear = 1880, qslot = "X1879.82", sex = "m")
mort.AT.census.1890.male = censtable(a.vz.dataM, name = "ÖVSt 1889/92 M", baseYear = 1890, qslot = "X1889.92", sex = "m")
mort.AT.census.1900.male = censtable(a.vz.dataM, name = "ÖVSt 1899/1902 M", baseYear = 1900, qslot = "X1899.1902", sex = "m")
mort.AT.census.1910.male = censtable(a.vz.dataM, name = "ÖVSt 1909/12 M", baseYear = 1910, qslot = "X1909.12", sex = "m")
mort.AT.census.1931.male = censtable(a.vz.dataM, name = "ÖVSt 1930/33 M", baseYear = 1931, qslot = "X1930.33", sex = "m")
mort.AT.census.1951.male = censtable(a.vz.dataM, name = "ÖVSt 1949/51 M", baseYear = 1951, qslot = "X1949.51", sex = "m")
mort.AT.census.1961.male = censtable(a.vz.dataM, name = "ÖVSt 1959/61 M", baseYear = 1961, qslot = "X1959.61", sex = "m")
mort.AT.census.1971.male = censtable(a.vz.dataM, name = "ÖVSt 1970/72 M", baseYear = 1971, qslot = "X1970.72", sex = "m")
mort.AT.census.1981.male = censtable(a.vz.dataM, name = "ÖVSt 1980/82 M", baseYear = 1981, qslot = "X1980.82", sex = "m")
mort.AT.census.1991.male = censtable(a.vz.dataM, name = "ÖVSt 1990/92 M", baseYear = 1991, qslot = "X1990.92", sex = "m")
mort.AT.census.2001.male = censtable(a.vz.dataM, name = "ÖVSt 2000/02 M", baseYear = 2001, qslot = "X2000.02", sex = "m")
mort.AT.census.2011.male = censtable(a.vz.dataM, name = "ÖVSt 2010/2012 M", baseYear = 2011, qslot = "X2010.12", sex = "m")
mort.AT.census.1869.female = censtable(a.vz.dataF, name="ÖVSt 1868/71 F", baseYear=1869, qslot="X1868.71", sex = "w")
mort.AT.census.1880.female = censtable(a.vz.dataF, name="ÖVSt 1879/82 F", baseYear=1880, qslot="X1879.82", sex = "w")
mort.AT.census.1890.female = censtable(a.vz.dataF, name="ÖVSt 1889/92 F", baseYear=1890, qslot="X1889.92", sex = "w")
mort.AT.census.1900.female = censtable(a.vz.dataF, name="ÖVSt 1899/1902 F", baseYear=1900, qslot="X1899.1902", sex = "w")
mort.AT.census.1910.female = censtable(a.vz.dataF, name="ÖVSt 1909/12 F", baseYear=1910, qslot="X1909.12", sex = "w")
mort.AT.census.1931.female = censtable(a.vz.dataF, name="ÖVSt 1930/33 F", baseYear=1931, qslot="X1930.33", sex = "w")
mort.AT.census.1951.female = censtable(a.vz.dataF, name="ÖVSt 1949/51 F", baseYear=1951, qslot="X1949.51", sex = "w")
mort.AT.census.1961.female = censtable(a.vz.dataF, name="ÖVSt 1959/61 F", baseYear=1961, qslot="X1959.61", sex = "w")
mort.AT.census.1971.female = censtable(a.vz.dataF, name="ÖVSt 1970/72 F", baseYear=1971, qslot="X1970.72", sex = "w")
mort.AT.census.1981.female = censtable(a.vz.dataF, name="ÖVSt 1980/82 F", baseYear=1981, qslot="X1980.82", sex = "w")
mort.AT.census.1991.female = censtable(a.vz.dataF, name="ÖVSt 1990/92 F", baseYear=1991, qslot="X1990.92", sex = "w")
mort.AT.census.2001.female = censtable(a.vz.dataF, name="ÖVSt 2000/02 F", baseYear=2001, qslot="X2000.02", sex = "w")
mort.AT.census.2011.female = censtable(a.vz.dataF, name="ÖVSt 2010/2012 F", baseYear=2011, qslot="X2010.12", sex = "w")
mort.AT.census.1869.female = censtable(a.vz.dataF, name = "ÖVSt 1868/71 F", baseYear = 1869, qslot = "X1868.71", sex = "w")
mort.AT.census.1880.female = censtable(a.vz.dataF, name = "ÖVSt 1879/82 F", baseYear = 1880, qslot = "X1879.82", sex = "w")
mort.AT.census.1890.female = censtable(a.vz.dataF, name = "ÖVSt 1889/92 F", baseYear = 1890, qslot = "X1889.92", sex = "w")
mort.AT.census.1900.female = censtable(a.vz.dataF, name = "ÖVSt 1899/1902 F", baseYear = 1900, qslot = "X1899.1902", sex = "w")
mort.AT.census.1910.female = censtable(a.vz.dataF, name = "ÖVSt 1909/12 F", baseYear = 1910, qslot = "X1909.12", sex = "w")
mort.AT.census.1931.female = censtable(a.vz.dataF, name = "ÖVSt 1930/33 F", baseYear = 1931, qslot = "X1930.33", sex = "w")
mort.AT.census.1951.female = censtable(a.vz.dataF, name = "ÖVSt 1949/51 F", baseYear = 1951, qslot = "X1949.51", sex = "w")
mort.AT.census.1961.female = censtable(a.vz.dataF, name = "ÖVSt 1959/61 F", baseYear = 1961, qslot = "X1959.61", sex = "w")
mort.AT.census.1971.female = censtable(a.vz.dataF, name = "ÖVSt 1970/72 F", baseYear = 1971, qslot = "X1970.72", sex = "w")
mort.AT.census.1981.female = censtable(a.vz.dataF, name = "ÖVSt 1980/82 F", baseYear = 1981, qslot = "X1980.82", sex = "w")
mort.AT.census.1991.female = censtable(a.vz.dataF, name = "ÖVSt 1990/92 F", baseYear = 1991, qslot = "X1990.92", sex = "w")
mort.AT.census.2001.female = censtable(a.vz.dataF, name = "ÖVSt 2000/02 F", baseYear = 2001, qslot = "X2000.02", sex = "w")
mort.AT.census.2011.female = censtable(a.vz.dataF, name = "ÖVSt 2010/2012 F", baseYear = 2011, qslot = "X2010.12", sex = "w")
mort.AT.census.2001.unisex = mortalityTable.mixed(table1=mort.AT.census.2001.male, table2=mort.AT.census.2001.female,
mort.AT.census.2001.unisex = mortalityTable.mixed(table1 = mort.AT.census.2001.male, table2 = mort.AT.census.2001.female,
data = list(
dim = list(sex = "u", collar = "Gesamtbevölkerung", type = "Volkssterbetafel Österreich", data = "official", year = 2001)
)
)
mort.AT.census.2011.unisex = censtable(a.vz.dataU, name = "ÖVSt 2010/2012 U", baseYear = 2011, qslot = "X2010.12", sex = "u")
mort.AT.census.ALL.male = MortalityTables::makeQxDataFrame(
mort.AT.census.1869.male,
......@@ -87,6 +89,6 @@ rm(a.vz.dataM, a.vz.dataF, censtable)
###############################################################################
# plot(mort.AT.census.ALL.male, title="Vergleich österreichische Sterbetafeln, Männer", legend.position=c(1,0))
# plot(mort.AT.census.ALL.female, title="Vergleich österreichische Sterbetafeln, Frauen", legend.position=c(1,0))
# plot(mort.AT.census.ALL.male, title = "Vergleich österreichische Sterbetafeln, Männer", legend.position = c(1,0))
# plot(mort.AT.census.ALL.female, title = "Vergleich österreichische Sterbetafeln, Frauen", legend.position = c(1,0))
......@@ -7,13 +7,13 @@ stopifnot(require(methods), require(utils), require(MortalityTables)) # Mortalit
###############################################################################
AT.pop.fc = utils::read.csv(system.file("extdata", "Austria_Population_Forecast.csv", package = "MortalityTables"), skip = 2);
AT.pop.fc = utils::read.csv(system.file("extdata", "Austria_Population_Forecast.csv", package = "MortalityTables"), skip = 2, encoding = "UTF-8");
mort.AT.forecast.male = mortalityTable.trendProjection(
name = "Österreich Männer (mittl. Sz.)",
baseYear = 2014,
deathProbs = AT.pop.fc$q.Männer.2014,
trend = -AT.pop.fc$Männer,
deathProbs = AT.pop.fc$q.M.2014,
trend = -AT.pop.fc$M,
ages = AT.pop.fc$X,
data = list(
dim = list(sex = "m", collar = "Gesamtbevölkerung", type = "Bevölkerungsprognose", data = "official", year = "2014-2080")
......@@ -22,8 +22,8 @@ mort.AT.forecast.male = mortalityTable.trendProjection(
mort.AT.forecast.female = mortalityTable.trendProjection(
name = "Österreich Frauen (mittl. Sz.)",
baseYear = 2014,
deathProbs = AT.pop.fc$q.Frauen.2014,
trend = -AT.pop.fc$Frauen,
deathProbs = AT.pop.fc$q.F.2014,
trend = -AT.pop.fc$F,
ages = AT.pop.fc$X,
data = list(
dim = list(sex = "w", collar = "Gesamtbevölkerung", type = "Bevölkerungsprognose", data = "official", year = "2014-2080")
......
......@@ -6,7 +6,11 @@
\alias{MortalityTables-package}
\title{Provide life table classes for life insurance purposes}
\description{
Provide life table classes for life insurance purposes
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.
}
\seealso{
Useful links:
......
......@@ -9,8 +9,9 @@
\usage{
calculateImprovements(object, ...)
\S4method{calculateImprovements}{mortalityTable.improvementFactors}(object, ...,
Period = NULL, YOB = 1982)
\S4method{calculateImprovements}{mortalityTable.improvementFactors}(object,
..., Period = NULL, YOB = 1982)
}
\arguments{
\item{object}{A pension table object (instance of a \code{\linkS4class{mortalityTable.improvementFactors}} class)}
......
......@@ -14,8 +14,8 @@
\usage{
deathProbabilities(object, ..., ages = NULL, YOB = 1975)
\S4method{deathProbabilities}{mortalityTable.period}(object, ..., ages = NULL,
YOB = 1975)
\S4method{deathProbabilities}{mortalityTable.period}(object, ...,
ages = NULL, YOB = 1975)
\S4method{deathProbabilities}{mortalityTable.ageShift}(object, ...,
ages = NULL, YOB = 1975)
......@@ -23,11 +23,11 @@ deathProbabilities(object, ..., ages = NULL, YOB = 1975)
\S4method{deathProbabilities}{mortalityTable.trendProjection}(object, ...,
ages = NULL, YOB = 1975)
\S4method{deathProbabilities}{mortalityTable.improvementFactors}(object, ...,
ages = NULL, YOB = 1975)
\S4method{deathProbabilities}{mortalityTable.improvementFactors}(object,
..., ages = NULL, YOB = 1975)
\S4method{deathProbabilities}{mortalityTable.mixed}(object, ..., ages = NULL,
YOB = 1975)
\S4method{deathProbabilities}{mortalityTable.mixed}(object, ...,
ages = NULL, YOB = 1975)
\S4method{deathProbabilities}{mortalityTable.jointLives}(object, ...,
ageDifferences = c(), ages = NULL, YOB = 1975)
......
......@@ -8,8 +8,8 @@
\usage{
mortalityImprovement(object, ..., Period = NULL, YOB = 1975)
\S4method{mortalityImprovement}{mortalityTable}(object, ..., Period = NULL,
YOB = 1975)
\S4method{mortalityImprovement}{mortalityTable}(object, ...,
Period = NULL, YOB = 1975)
}
\arguments{
\item{object}{The life table object (class inherited from mortalityTable)}
......
......@@ -4,8 +4,8 @@
\alias{mortalityTable.once}
\title{Generate a (deterministic) mortality table with only one probability set to 1 (for the given age)}
\usage{
mortalityTable.once(transitionAge, name = "Deterministic mortality table",
ages = 0:99)
mortalityTable.once(transitionAge,
name = "Deterministic mortality table", ages = 0:99)
}
\arguments{
\item{transitionAge}{The age where the deterministic transition occurs}
......
......@@ -21,10 +21,12 @@ periodDeathProbabilities(object, ..., ages = NULL, Period = 1975)
\S4method{periodDeathProbabilities}{mortalityTable.ageShift}(object, ...,
ages = NULL, Period = 1975)
\S4method{periodDeathProbabilities}{mortalityTable.trendProjection}(object, ...,
ages = NULL, Period = 1975)
\S4method{periodDeathProbabilities}{mortalityTable.improvementFactors}(object,
\S4method{periodDeathProbabilities}{mortalityTable.trendProjection}(object,
..., ages = NULL, Period = 1975)
\S4method{periodDeathProbabilities}{mortalityTable.improvementFactors}(object,
..., ages = NULL, Period = 1975)
\S4method{periodDeathProbabilities}{mortalityTable.mixed}(object, ...,
......
......@@ -8,9 +8,10 @@
\usage{
periodTransitionProbabilities(object, ...)
\S4method{periodTransitionProbabilities}{pensionTable}(object, Period = 2017,
..., ages = NULL, OverallMortality = FALSE, retirement = NULL,
invalids.retire = object@invalids.retire, as.data.frame = TRUE)
\S4method{periodTransitionProbabilities}{pensionTable}(object,
Period = 2017, ..., ages = NULL, OverallMortality = FALSE,
retirement = NULL, invalids.retire = object@invalids.retire,
as.data.frame = TRUE)
}
\arguments{
\item{object}{A pension table object (instance of a \code{\linkS4class{pensionTable}} class)}
......
......@@ -5,10 +5,10 @@
\title{Plot multiple mortality tables (life tables) in one plot}
\usage{
plotMortalityTables(data, ..., aes = NULL, ages = NULL,
legend.title = "Sterbetafel", xlim = NULL, ylim = NULL, xlab = NULL,
ylab = NULL, title = "", legend.position = c(0.9, 0.1),
legend.justification = c(1, 0), legend.key.width = unit(25, "mm"),
log = TRUE)
legend.title = "Sterbetafel", xlim = NULL, ylim = NULL,
xlab = NULL, ylab = NULL, title = "", legend.position = c(0.9,
0.1), legend.justification = c(1, 0), legend.key.width = unit(25,
"mm"), log = TRUE)
}
\arguments{
\item{data}{First life table to be plotted. Either a \code{data.frame} generated by \code{makeQxDataFrame} or a \code{mortalityTable} object}
......