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Plot projection output.

Usage

# S3 method for SUMMERproj
plot(
  x,
  year_label = c("85-89", "90-94", "95-99", "00-04", "05-09", "10-14", "15-19"),
  year_med = c(1987, 1992, 1997, 2002, 2007, 2012, 2017),
  is.subnational = TRUE,
  proj_year = 2015,
  data.add = NULL,
  option.add = list(point = NULL, lower = NULL, upper = NULL, by = NULL),
  color.add = "black",
  label.add = NULL,
  dodge.width = 1,
  plot.CI = NULL,
  per1000 = FALSE,
  color.CI = NULL,
  alpha.CI = 0.5,
  ...
)

Arguments

x

output from getSmoothed

year_label

labels for the periods

year_med

labels for the middle years in each period, only used when both yearly and period estimates are plotted. In that case, year_med specifies where each period estimates are aligned.

is.subnational

logical indicator of whether the data contains subnational estimates

proj_year

the first year where projections are made, i.e., where no data are available.

data.add

data frame for the Comparisons data points to add to the graph. This can be, for example, the raw direct estimates. This data frame is merged to the projections by column 'region' and 'years'. Except for these two columns, this dataset should not have Comparisons columns with names overlapping the getSmoothed output.

option.add

list of options specifying the variable names for the points to plot, lower and upper bounds, and the grouping variable. This is intended to be used to add Comparisons estimates on the same plot as the smoothed estimates. See examples for details.

color.add

the color of the Comparisons data points to plot.

label.add

the label of the Comparisons data points in the legend.

dodge.width

the amount to add to data points at the same year to avoid overlap. Default to be 1.

plot.CI

logical indicator of whether to plot the error bars.

per1000

logical indicator to plot mortality rates as rates per 1,000 live births. Note that the added comparison data should always be in the probability scale.

color.CI

the color of the error bars of the credible interval.

alpha.CI

the alpha (transparency) of the error bars of the credible interval.

...

optional arguments, see details

See also

Author

Zehang Richard Li

Examples

if (FALSE) {
years <- levels(DemoData[[1]]$time)

# obtain direct estimates
data <- getDirectList(births = DemoData, 
years = years,  
regionVar = "region", timeVar = "time", 
clusterVar = "~clustid+id", 
ageVar = "age", weightsVar = "weights", 
geo.recode = NULL)
# obtain direct estimates
data_multi <- getDirectList(births = DemoData, years = years,
  regionVar = "region",  timeVar = "time", clusterVar = "~clustid+id",
  ageVar = "age", weightsVar = "weights", geo.recode = NULL)
data <- aggregateSurvey(data_multi)

#  national model
years.all <- c(years, "15-19")
fit1 <- smoothDirect(data = data, geo = NULL, Amat = NULL, 
  year_label = years.all, year_range = c(1985, 2019), 
  rw = 2, is.yearly=FALSE, m = 5)
out1 <- getSmoothed(fit1)
plot(out1, is.subnational=FALSE)

#  subnational model
fit2 <- smoothDirect(data = data, geo = geo, Amat = mat, 
  year_label = years.all, year_range = c(1985, 2019), 
  rw = 2, is.yearly=TRUE, m = 5, type.st = 4)
out2 <- getSmoothed(fit2)
plot(out2, is.yearly=TRUE, is.subnational=TRUE)


}