emdiObject: Fitted emdiObject

In akreutzmann/fayherriot:

Description

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 standard Fay-Herriot approach ("fh"), and the empirical best prediction ("ebp"). Objects of these classes have methods for the generic functions estimators, print, plot (only for class model), and summary.

Value

The following components are always included in an emdi object:

call	a list containing an image of the function call that produced the object.
fixed	a formula of fixed effects used in the nested error linear regression (see also fixed in fh and ebp). Not filled for class direct.
framework	a list with following components:

	N_dom_smp	number of domains in the sample.
	N_dom_unobs	number of out-of-sample domains. Not filled for class direct.
	N_pop	total number of units in population. Not filled for class direct.
	N_smp	total number of units in sample.
	pop_domains_vec	an arranged vector of the domain indicator variable. Not filled for class direct.
	smp_data	an arranged data set of sample data. Not filled for class direct.
	smp_domains	a character naming the domain indicator variable.
	smp_domains_vec	an arranged vector of the domain indicator variable.

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	for class ebp, an object returned by the lme function of type "lme" and representing a fitted linear mixed-effects model (for further explanations see lme and lmeObject). For class fh, 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 returning the selected transformation type (see also transformation in fh, and ebp). 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	a matrix with domains as rows and indicators as columns. The cells contain the number of successful bootstraps for each combination. Not filled for class model.

References

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–Stein procedures to census data. Journal of the American Statistical Association, Vol. 74, 269–277.

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.

See Also

direct, ebp, lme, lmeObject

akreutzmann/fayherriot documentation built on Aug. 19, 2019, 12:22 p.m.