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Visualizes disaggregated estimates on a map

Source: R/map_indicators.R
map_indicators.Rd

Function map_indicators visualizes estimates from a SAEforestObject on a specified map. The function can be seen as a modified wrapper of map_plot from the package emdi.

Usage

map_indicators(
  object,
  indicator = "all",
  MSE = FALSE,
  CV = FALSE,
  map_obj = NULL,
  map_dom_id = NULL,
  map_tab = NULL,
  color = c("white", "darkgreen"),
  scale_points = NULL,
  guide = "colourbar",
  return_data = FALSE,
  return_plot = FALSE,
  gg_theme = theme_minimal()
)

Arguments

object

An object of class SAEforest, containing estimates to be visualized.

indicator

Optional character vector specifying indicators to be mapped: (i) all calculated indicators ("all"); (ii) default indicators name: "Mean", "Quant10", "Quant25", "Median", "Quant75", "Quant90", "Gini", "Hcr", "Pgap", "Qsr" or the function name/s of "custom_indicator/s"; (iii) a vector of names of indicators. If the object is estimated with option meanOnly = TRUE, indicator arguments are ignored and only "Mean" is visualized.

MSE

Logical. If TRUE, the MSE is also visualized. Defaults to FALSE.

CV

Logical. If TRUE, the CV is also visualized. Defaults to FALSE.

map_obj

An "sf", "data.frame" object as defined by the sf package on which the data should be visualized.

map_dom_id

Character string containing the name of a variable in map_obj that indicates the domains.

map_tab

A data.frame object with two columns that matches the domain variable from the population data set (first column) with the domain variable in the map_obj (second column). This should only be used if domain-level identifiers are different in both objects.

color

A vector of length 2 defining the lowest and highest color in the map.

scale_points

A structure defining the lowest, the mid and the highest value of the colorscale. If a numeric vector of length two is given, this scale will be used for every plot. Alternatively, a list defining colors for each plot separately may be given.

guide

Character passed to scale_colour_gradient from ggplot2. Possible values are "none", "colourbar", and "legend".

return_data

If set to TRUE, a fortified data frame including the map data as well as the chosen indicators is returned. Customized maps can easily be obtained from this data frame via the package ggplot2. Defaults to FALSE.

return_plot

If set to TRUE, a list of individual plots produced by ggplot2 is returned for further individual customization and processing.

gg_theme

Specify a predefined theme from ggplot2. Defaults to theme_minimal.

Value

Creates required plots and if selected, a fortified data.frame and a list of plots.

See also

SAEforest, sf, ggplot.

Examples

# \donttest{
# Loading data
data("eusilcA_pop")
data("eusilcA_smp")

# Load shape file
load_shapeaustria()

income <- eusilcA_smp$eqIncome
X_covar <- eusilcA_smp[, -c(1, 16, 17, 18)]

# Example 1:
# Calculating point estimates and discussing basic generic functions

model1 <- SAEforest_model(Y = income, X = X_covar, dName = "district",
                          smp_data = eusilcA_smp, pop_data = eusilcA_pop,
                          num.trees = 50)
#> Error in initializePtr(): function 'cholmod_factor_ldetA' not provided by package 'Matrix'

# Create map plot for mean indicator - point and MSE estimates but no CV

map_indicators(object = model1, MSE = FALSE, CV = FALSE, map_obj = shape_austria_dis,
                          indicator = c("Mean"), map_dom_id = "PB")
#> Error in eval(expr, envir, enclos): object 'model1' not found

# Create a suitable mapping table to use numerical identifiers of the shape
# file

# First find the right order
dom_ord <- match(shape_austria_dis$PB, model1$Indicators$district)
#> Error in eval(expr, envir, enclos): object 'model1' not found

# Create the mapping table based on the order obtained above
map_tab <- data.frame(pop_data_id = model1$Indicators$district[dom_ord],
                      shape_id = shape_austria_dis$BKZ)
#> Error in eval(expr, envir, enclos): object 'model1' not found

# Create map plot for mean indicator - using the numerical domain
# identifiers of the shape file. Additionally save the figure in as a list element.

map_obj <- map_indicators(object = model1, MSE = FALSE, CV = FALSE,
                          map_obj = shape_austria_dis, indicator = c("Mean"),
                          map_dom_id = "BKZ", map_tab = map_tab, return_plot = TRUE)
#> Error in eval(expr, envir, enclos): object 'model1' not found
# }