emdi (version 1.1.1)

summary.emdi: Summarize an emdiObject

Description

Additional information about the data and model in small area estimation methods and components of an emdi object are extracted. The returned object is suitable for printing with the print.summary.emdi method.

Usage

# S3 method for emdi
summary(object, ...)

Arguments

object

an object of type "emdi", representing point and MSE estimates. Objects differ depending on the estimation method: direct vs. model-based.

...

additional arguments that are not used in this method

Value

an object of type "summary.emdi" with following components:

out_of_smp

if model-based estimation, number of out-of-sample domains equivalent to N_dom_unobs (see emdiObject).

in_smp

number of in-sample domains equivalent to N_dom_smp (see emdiObject).

size_smp

number of units in sample equivalent to N_smp (see emdiObject).

size_pop

if model-based estimation, number of units in population equivalent to N_pop (see emdiObject).

size_dom

a data frame with rows Sample_domains and Population_domains (if model-based estimation) representing summary statisitics of the sample sizes across domains of sample and population data, respectively.

transform

if model-based estimation, a data frame with columns Transformation, Method, Optimal_lambda and Shift_parameter representing the chosen transformation type and estimation method for lambda as well as their results.

normality

if model-based estimation, a data frame with columns Skewness, Kurtosis, Shapiro_W and Shapiro_p where the latter two represent the results of a Shapiro-Wilks-Test for normality. Rows correspond to Pearson residuals and random effects of the nested error regression model. The functions skewness and kurtosis are from the package moments. Details for the Shapiro-Wilks-Test are provided by shapiro.test.

icc

if model-based estimation, the value of the intraclass coefficient.

coeff_determ

if model-based estimation, a data frame with colums Marginal_R2 and Conditional_R2 representing two R2 measures for linear mixed models from the MuMin package obtained by function r.squaredGLMM.

call

a list containing an image of the function call that produced the object.

See Also

emdiObject, direct, ebp, r.squaredGLMM, skewness, kurtosis, shapiro.test

Examples

# NOT RUN {
# 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, threshold){max(y)},
my_min = function(y, threshold){min(y)}), na.rm = TRUE, cpus = 1)

# Receive first overview
summary(emdi_model)
# }