| map_plot {emdi} | R Documentation | 
Visualizes regional disaggregated estimates on a map
Description
Function map_plot creates spatial visualizations of the estimates
obtained by small area estimation methods.
Usage
map_plot(
  object,
  indicator = "all",
  MSE = FALSE,
  CV = FALSE,
  map_obj = NULL,
  map_dom_id = NULL,
  map_tab = NULL,
  color = c("white", "red4"),
  scale_points = NULL,
  guide = "colourbar",
  return_data = FALSE
)
Arguments
| object | an object of type emdi, containing the estimates to be visualized. | 
| indicator | optional character vector that selects which indicators
shall be returned: (i) all calculated indicators ("all");
(ii) each indicator name: "Mean", "Quantile_10", "Quantile_25", "Median",
"Quantile_75", "Quantile_90", "Head_Count", "Poverty_Gap", "Gini",
"Quintile_Share" or the function name/s of "custom_indicator/s";
(iii) groups of indicators: "Quantiles", "Poverty" or
"Inequality". Note, additional custom indicators can be
defined as argument for model-based approaches (see also  | 
| MSE | optional logical. If  | 
| CV | optional logical. If  | 
| map_obj | an  | 
| map_dom_id | a character string containing the name of a variable in
 | 
| map_tab | a  | 
| color | a  | 
| scale_points | a structure defining the lowest and the highest value of the colorscale. If a numeric vector of length two is given, this scale will be used for every plot. | 
| guide | character passed to
 | 
| return_data | if set to  | 
Value
Creates the plots demanded, and, if selected, a fortified data.frame containing the mapdata and chosen indicators.
See Also
direct, ebp, fh,
emdiObject, sf
Examples
data("eusilcA_pop")
data("eusilcA_smp")
# Generate emdi object with additional indicators; here via function ebp()
emdi_model <- ebp(
  fixed = eqIncome ~ gender + eqsize + cash +
    self_empl + unempl_ben + age_ben + surv_ben + sick_ben +
    dis_ben + rent + fam_allow + house_allow + cap_inv +
    tax_adj, pop_data = eusilcA_pop,
  pop_domains = "district", smp_data = eusilcA_smp,
  smp_domains = "district", threshold = 11064.82,
  transformation = "box.cox", L = 50, MSE = TRUE, B = 50
)
# Load shape file
load_shapeaustria()
# Create map plot for mean indicator - point and MSE estimates but no CV
map_plot(
  object = emdi_model, MSE = TRUE, CV = FALSE,
  map_obj = shape_austria_dis, 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_austria_dis$PB, emdi_model$ind$Domain)
#Create the mapping table based on the order obtained above
map_tab <- data.frame(pop_data_id = emdi_model$ind$Domain[dom_ord],
                      shape_id = shape_austria_dis$BKZ)
# Create map plot for mean indicator - point and CV estimates but no MSE
# using the numerical domain identifiers of the shape file
map_plot(
  object = emdi_model, MSE = FALSE, CV = TRUE,
  map_obj = shape_austria_dis, indicator = c("Mean"),
  map_dom_id = "BKZ", map_tab = map_tab
)