SUMMER (version 0.2.3)

plot.projINLA: Plot projection output.

Description

Plot projection output.

Usage

# S3 method for projINLA
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.yearly = TRUE, is.subnational = TRUE,
  proj_year = 2015, data.add = NULL, option.add = list(point = NULL,
  lower = NULL, upper = NULL, by = NULL), color.add = "black",
  dodge.width = 1, ...)

Arguments

x

output from projINLA

year_label

labels for the periods

year_med

labels for the middle years in each period

is.yearly

logical indicator of whether the data contains yearly estimates

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 projINLA 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.

dodge.width

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

...

optional arguments, see details

Details

Note that arguments after ... must match exactly.

• year_labelstring of year labels, defaults to c("85-89", "90-94", "95-99", "00-04", "05-09", "10-14", "15-19")

• proj_yearprojection year as numeric, defaults to 2015

• year_med median of year intervals, defaults to c(1987, 1992, 1997, 2002, 2007, 2012, 2017)

• is.yearlyindicator for yearly model, defaults to TRUE

• is.subnationalindicator for subnational model, defaults to TRUE

Examples

# NOT RUN {
data(DemoData)
deta(DemoMap)
years <- levels(DemoData[[1]]$time)

data <- countrySummary_mult(births = DemoData, 
years = years, 
regionVar = "region", timeVar = "time", 
clusterVar = "~clustid+id", 
ageVar = "age", weightsVar = "weights", 
geo.recode = NULL)

# obtain maps
geo <- DemoMap$geo
mat <- DemoMap$Amat

# combine data from multiple surveys
data_agg <- aggregateSurvey(data)

# Model fitting with INLA
years.all <- c(years, "15-19")


fit <- fitINLA(data = data_agg, geo = NULL, Amat = NULL, 
year_names = years.all, year_range = c(1985, 2019),  
rw = 2, is.yearly=TRUE, 
m = 5, type.st = 4)
# Projection
out <- projINLA(fit, is.yearly = TRUE)
# National smoothed plot
plot(out, is.yearly=TRUE, is.subnational=FALSE) + ggplot2::ggtitle("National yearly model")

# National smoothed plot with the aggregated direct estimates
plot(out, is.yearly=TRUE, is.subnational=FALSE,  data.add = data_agg, 
option.add = list(point = "u5m", lower = "lower", upper = "upper"), 
color.add = "orange") + ggplot2::ggtitle("National yearly model") 

# National smoothed plot with the survey-specific direct estimates
plot(out, is.yearly=TRUE, is.subnational=FALSE,  data.add = data, 
option.add = list(point = "u5m", by = "surveyYears"), 
color.add = "darkblue") + ggplot2::ggtitle ("National yearly model") 



fit <- fitINLA(data = data_agg, geo = geo, Amat = mat, 
year_names = years.all, year_range = c(1985, 2019),  
rw = 2, is.yearly=TRUE, 
m = 5, type.st = 4)
# Projection
out <- projINLA(fit, Amat = mat, is.yearly = TRUE)

# Subnational estimates
plot(out, is.yearly=TRUE, is.subnational=TRUE) + ggplot2::ggtitle("Subnational yearly model")


# Subnational estimates with the aggregated direct estimates
plot(out, is.yearly=TRUE, is.subnational=TRUE,  data.add = data_agg, option.add = 
list(point = "u5m", lower = "lower", upper = "upper")) + 
ggplot2::ggtitle("Subnational yearly model") + facet_wrap(~region)


# Subnational estimates with survey-specific direct estimates
plot(out, is.yearly=TRUE, is.subnational=TRUE,  data.add = data, option.add = 
list(point = "u5m", by = "surveyYears")) + 
ggplot2::ggtitle("Subnational yearly model") + facet_wrap(~region) 


# }