R/rsaeGWG.R

In baldermann/rsaeGWR: Robust small area estimation under spatial non-stationarity

#' rsaeGWR: A package for robust small area estimation under spatial non-stationarity
#'
#' The package provides two categories of important functions:
#' fit and predict.
#'
#' @section The fit functions:
#' The fit functions \code{\link{gwlmm}} and \code{\link{rgwlmm}} fit a geographically weighted
#' linear mixed model (GWLMM) to data. The GWLMM is a nested error regression model that takes
#' into account spatial non-stationarity. The function \code{\link{gwlmm}} assumes normality
#' for the error term components. This assumption can be violated in the presence
#' of outliers. The function \code{\link{rgwlmm}} fits an outlier robust version of the GWLMM to the data.
#'
#' @section The predrict function:
#' The predict functions \code{\link{predict.gwlmm}} and \code{\link{predict.rgwlmm}} estimate
#' small area means based on the model fits from the fit funtions when population data is provided.
#' As predcision measures MSE estiamtes are provided.
#' The predict functions can handle aggregated population information with centroid coordinates and
#'  unit-level population data with coordinates for each unit.
#' If no data is provided these functions provide the in-sample predictions
#' (random effects, residuals, etc.) based on the model fits.
#'
#'
#' @docType package
#' @name rsaeGWR
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