Produces plots of rates versus age, connected within period or cohort
(Aplot
), rates versus period connected within age-groups
(Pplot
) and rates and rates versus date of birth cohort
(Cplot
). rateplot
is a wrapper for these, allowing
to produce the four classical displays with a single call.
rateplot( rates,
which = c("ap","ac","pa","ca"),
age = as.numeric( dimnames( rates )[[1]] ),
per = as.numeric( dimnames( rates )[[2]] ),
grid = FALSE,
a.grid = grid,
p.grid = grid,
c.grid = grid,
ygrid = grid,
col.grid = gray( 0.9 ),
a.lim = range( age, na.rm=TRUE ) + c(0,diff( range( age ) )/30),
p.lim = range( per, na.rm=TRUE ) + c(0,diff( range( age ) )/30),
c.lim = NULL,
ylim = range( rates[rates>0], na.rm=TRUE ),
at = NULL,
labels = paste( at ),
a.lab = "Age at diagnosis",
p.lab = "Date of diagnosis",
c.lab = "Date of birth",
ylab = "Rates",
type = "l",
lwd = 2,
lty = 1,
log.ax = "y",
las = 1,
ann = FALSE,
a.ann = ann,
p.ann = ann,
c.ann = ann,
xannx = 1/20,
cex.ann = 0.8,
a.thin = seq( 1, length( age ), 2 ),
p.thin = seq( 1, length( per ), 2 ),
c.thin = seq( 2, length( age ) + length( per ) - 1, 2 ),
col = par( "fg" ),
a.col = col,
p.col = col,
c.col = col,
... )Aplot( rates, age = as.numeric( dimnames( rates )[[1]] ),
per = as.numeric( dimnames( rates )[[2]] ), grid = FALSE,
a.grid = grid, ygrid = grid, col.grid = gray( 0.9 ),
a.lim = range( age, na.rm=TRUE ), ylim = range( rates[rates>0], na.rm=TRUE ),
at = NULL, labels = paste( at ), a.lab = names( dimnames( rates ) )[1],
ylab = deparse( substitute( rates ) ), type = "l", lwd = 2, lty = 1,
col = par( "fg" ), log.ax = "y", las = 1, c.col = col, p.col = col,
c.ann = FALSE, p.ann = FALSE, xannx = 1/20, cex.ann = 0.8,
c.thin = seq( 2, length( age ) + length( per ) - 1, 2 ),
p.thin = seq( 1, length( per ), 2 ), p.lines = TRUE,
c.lines = !p.lines, ... )
Pplot( rates, age = as.numeric( dimnames( rates )[[1]] ),
per = as.numeric( dimnames( rates )[[2]] ), grid = FALSE,
p.grid = grid, ygrid = grid, col.grid = gray( 0.9 ),
p.lim = range( per, na.rm=TRUE ) + c(0,diff(range(per))/30),
ylim = range( rates[rates>0], na.rm=TRUE ), p.lab = names( dimnames( rates ) )[2],
ylab = deparse( substitute( rates ) ), at = NULL, labels = paste( at ),
type = "l", lwd = 2, lty = 1, col = par( "fg" ), log.ax = "y",
las = 1, ann = FALSE, cex.ann = 0.8, xannx = 1/20,
a.thin = seq( 1, length( age ), 2 ), ... )
Cplot( rates, age = as.numeric( rownames( rates ) ),
per = as.numeric( colnames( rates ) ), grid = FALSE,
c.grid = grid, ygrid = grid, col.grid = gray( 0.9 ),
c.lim = NULL, ylim = range( rates[rates>0], na.rm=TRUE ),
at = NULL, labels = paste( at ), c.lab = names( dimnames( rates ) )[2],
ylab = deparse( substitute( rates ) ), type = "l", lwd = 2, lty = 1,
col = par( "fg" ), log.ax = "y", las = 1, xannx = 1/20, ann = FALSE,
cex.ann = 0.8, a.thin = seq( 1, length( age ), 2 ), ... )
A two-dimensional table (or array) with rates to be plotted. It is assumed that the first dimension is age and the second is period.
A character vector with elements from
c("ap","ac","apc","pa","ca")
, indication which plots should
be produced. One plot per element is produced. The first letter
indicates the x-axis of the plot, the remaining which groups
should be connected, i.e. "pa"
will plot rates versus
period and connect age-classes, and "apc"
will plot rates
versus age, and connect both periods and cohorts.
Numerical vector giving the means of the
age-classes. Defaults to the rownames of rates
as numeric.
Numerical vector giving the means of the periods. Defaults
to the columnnames of rates
as numeric.
Logical indicating whether a background grid should be drawn.
Logical indicating whether a background grid on the age-axis should be drawn. If numerical it indicates the age-coordinates of the grid.
do. for the period.
do. for the cohort.
do. for the rate-dimension.
The colour of the grid.
Range for the age-axis.
Range for the period-axis.
Range for the cohort-axis.
Range for the y-axis (rates).
Position of labels on the y-axis (rates).
Labels to put on the y-axis (rates).
Text on the age-axis. Defaults to "Age".
Text on the period-axis. Defaults to "Date of diagnosis".
Text on the cohort-axis. Defaults to "Date of birth".
Text on the rate-axis. Defaults to the name of the rate-table.
How should the curves be plotted. Defaults to "l"
.
Width of the lines. Defaults to 2.
Which type of lines should be used. Defaults to 1, a solid line.
Character with letters from "apcyr"
, indicating
which axes should be logarithmic. "y"
and "r"
both
refer to the rate scale. Defaults to "y"
.
see par
.
Should the curves be annotated?
Logical indicating whether age-curves should be annotated.
do. for period-curves.
do. for cohort-curves.
The fraction that the x-axis is expanded when curves are annotated.
Expansion factor for characters annotating curves.
Vector of integers indicating which of the age-classes should be labelled.
do. for the periods.
do. for the cohorts.
Colours for the curves.
Colours for the age-curves.
do. for the period-curves.
do. for the cohort-curves.
Should rates from the same period be connected?
Should rates from the same cohort be connected?
Additional arguments pssed on to matlines
when
plotting the curves.
NULL
. The function is used for its side-effect, the plot.
Zero values of the rates are ignored. They are neiter in the plot nor in the calculation of the axis ranges.
# NOT RUN {
data( blcaIT )
attach(blcaIT)
# Table of rates:
bl.rate <- tapply( D, list(age,period), sum ) /
tapply( Y, list(age,period), sum )
bl.rate
# The four classical plots:
par( mfrow=c(2,2) )
rateplot( bl.rate*10^6 )
# The labels on the vertical axis could be nicer:
rateplot( bl.rate*10^6, at=10^(-1:3), labels=c(0.1,1,10,100,1000) )
# More bells an whistles
par( mfrow=c(1,3), mar=c(3,3,1,1), oma=c(0,3,0,0), mgp=c(3,1,0)/1.6 )
rateplot( bl.rate*10^6, ylab="", ann=TRUE, which=c("AC","PA","CA"),
at=10^(-1:3), labels=c(0.1,1,10,100,1000),
col=topo.colors(11), cex.ann=1.2 )
# }
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