An object of class emdi that represents point predictions of regional
disaggregated indicators. Optionally, it also contains corresponding MSE
estimates. Depending on the estimation, the object is also of class direct
or model. For each provided model-based approach, an additional class is assigned:
the Fay-Herriot approach ("fh"), and the empirical best prediction
("ebp"). Objects of these classes have methods for the generic functions
compare
, compare_plot
, estimators
,
print
, plot
(only for class model), and
summary
.
The following components are always included in an emdi object but not always filled and with different components depending on the estimation approach:
call
the function call that produced the object.
fixed
for details, see fixed
in fh
and
ebp
. Not filled for class direct.
framework
a list with components that describe the data setup, e.g., number of domains in the sample.
ind
data frame containing estimates for indicators per domain.
method
character returning the method for the estimation of the optimal lambda (for class ebp), here "reml", or a list returning method for the estimation of the variance of the random effect and the applied MSE estimation (for class fh). Not filled for class direct.
model
list containing a selection of model components. Not filled for class direct.
MSE
data frame containing MSE estimates corresponding to the
point predictions in ind
per indicator per domain if MSE is selected
in function call. If FALSE
, MSE
is NULL
.
transformation
character or list containing information about applied transformation and, if appropriate, backtransformation. Not filled for class direct.
transform_param
a list with two elements, optimal_lambda
and shift_par
, where the first contains the optimal parameter for a
Box-Cox transformation or NULL for no and log transformation and the
second the potential shift parameter in the log or Box-Cox transformation
and NULL for no transformation. Not filled for class fh and direct.
successful_bootstraps
for class direct, a matrix with domains as rows and indicators as columns. The cells contain the number of successful bootstraps for each combination. For non-robust spatial Fay-Herriot, string with number of successful bootstraps. Not filled for other models in class model.
Alfons, A. and Templ, M. (2013). Estimation of Social Exclusion Indicators from Complex Surveys: The R Package laeken. Journal of Statistical Software, 54(15), 1-25. Fay R.E., Herriot R.A. (1979) Estimates of income for small places: An application of James<U+2013>Stein procedures to census data. Journal of the American Statistical Association, Vol. 74, 269<U+2013>277. Molina, I. and Rao, J.N.K. (2010). Small area estimation of poverty indicators. The Canadian Journal of Statistics, Vol. 38, No.3, 369-385.