map_indicators: Visualizes disaggregated estimates on a map
In SAEforest: Mixed Effect Random Forests for Small Area Estimation

map_indicators

R Documentation

Visualizes disaggregated estimates on a map

Description

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 `SpatialPolygonsDataFrame` object as defined by the sp 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.

Examples


# Loading data
data("eusilcA_pop")
data("eusilcA_smp")
data("shape_Aut")

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)

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

map_indicators(object = model1, MSE = FALSE, CV = FALSE, map_obj = shape_Aut,
               indicator = c("Mean"), map_dom_id = "PB")

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

# First find the right order
dom_ord <- match(shape_Aut@data$PB, model1$Indicators$district)

# 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_Aut@data$BKZ)

# 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_Aut, indicator = c("Mean"),
                          map_dom_id = "BKZ", map_tab = map_tab, return_plot = TRUE)

SAEforest documentation built on Sept. 8, 2022, 1:05 a.m.