emdi_summaries: Summarizes an emdiObject

Description

Additional information about the data and model in small area estimation methods and components of an emdi object are extracted. The generic function summary has methods for classes "direct", "ebp" and "fh" and the returned object is suitable for printing with the print.

Usage

# S3 method for direct
summary(object, ...)
# S3 method for ebp
summary(object, ...)
# S3 method for fh
summary(object, ...)

Value

an object of type "summary.direct", "summary.ebp" or "summary.fh" with information about the sample and population data, the usage of transformation, normality tests and information of the model fit.

Arguments

object: an object of type "direct", "ebp" or "fh", representing point and MSE estimates. Objects differ depending on the estimation method.
...: additional arguments that are not used in this method.

References

Lahiri, P. and Suntornchost, J. (2015), Variable selection for linear mixed models with applications in small area estimation, The Indian Journal of Statistics 77-B(2), 312-320.

Marhuenda, Y., Morales, D. and Pardo, M.C. (2014). Information criteria for Fay-Herriot model selection. Computational Statistics and Data Analysis 70, 268-280.

Nakagawa S, Schielzeth H (2013). A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods in Ecology and Evolution, 4(2), 133-142.

Examples

Run this code

# \donttest{
# Example for models of type ebp

# Loading data - population and sample data
data("eusilcA_pop")
data("eusilcA_smp")

# Example with two additional indicators
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 = function(y) {
    0.6 * median(y)
  }, L = 50, MSE = TRUE, B = 50,
  custom_indicator = list(
    my_max = function(y) {
      max(y)
    },
    my_min = function(y) {
      min(y)
    }
  ), na.rm = TRUE, cpus = 1
)

# Example 1: Receive first overview
summary(emdi_model)


# Example for models of type fh

# Loading data - population and sample data
data("eusilcA_popAgg")
data("eusilcA_smpAgg")

# Combine sample and population data
combined_data <- combine_data(
  pop_data = eusilcA_popAgg,
  pop_domains = "Domain",
  smp_data = eusilcA_smpAgg,
  smp_domains = "Domain"
)

# Generation of the emdi object
fh_std <- fh(
  fixed = Mean ~ cash + self_empl, vardir = "Var_Mean",
  combined_data = combined_data, domains = "Domain",
  method = "ml", MSE = TRUE
)

# Example 2: Receive first overview
summary(fh_std)
# }