Package index • fastsae

Classical Area-Level Models (EBLUP)

High-performance C++ implementation of Fay-Herriot models

eblup_fh(): Empirical Best Linear Unbiased Prediction based on a Fay-Herriot Model.
eblup_sfh(): Empirical Best Linear Unbiased Prediction based on a Spatial Fay-Herriot Model.
eblup_stfh(): Empirical Best Linear Unbiased Prediction based on a Spatio-Temporal Fay-Herriot Model.

Hierarchical Bayesian Small Area Estimation using INLA across 6 distributions with spatial and spatio-temporal effects

Battese-Harter-Fuller model for unit-level survey data

eblup_bhf(): Empirical Best Linear Unbiased Prediction (EBLUP) for the Battese-Harter-Fuller Model

Universal diagnostic framework and ggplot2 visualization methods

diagnose(): Diagnostic Evaluation of Small Area Estimation Models
autoplot(<fastsae_diagnose>): Autoplot Method for fastsae_diagnose Objects
autoplot(<fastsae>) autoplot(<list>): Autoplot Method for fastsae Objects
summary(<fastsae>): Summarize a fastsae object
coef(<fastsae>): Extract coefficients from a fastsae object
fitted(<fastsae>): Extract fitted values (EBLUP or HB) from a fastsae object
residuals(<fastsae>): Extract residuals from a fastsae object
print(<fastsae>): Print a fastsae object
print(<summary.fastsae>): Print summary of a fastsae object

Calibrate small area estimates to aggregate targets via Ratio, Difference, Optimal, and Logit methods (Rao & Molina, 2015)

benchmark_sae() benchmark() print(<fastsae_benchmark>) summary(<fastsae_benchmark>) autoplot(<fastsae_benchmark>) plot(<fastsae_benchmark>): Benchmark Small Area Estimation Predictions to Aggregate Targets

Unified spatial choropleth mapping (‘satu pintu’), model concordance evaluation, and official publication exports

map_sae(): Unified Spatial Choropleth Mapping for Small Area Estimates
compare_sae() print(<fastsae_comparison>) summary(<fastsae_comparison>) plot(<fastsae_comparison>) autoplot(<fastsae_comparison>): Compare Two Small Area Estimation Models
export_sae(): Export Small Area Estimation Results to Excel or CSV
add_reliability_flags(): Add Official Statistical Reliability Flags
plot(<fastsae>): Plot method for fastsae objects

Utilities to simulate area-level cross-sectional, panel, and spatial weight matrices

sim_area_data(): Simulate Multi-Distribution Small Area Data with Spatial Autocorrelation
sim_series_data(): Simulate Spatio-Temporal Multi-Distribution Small Area Data
sim_spatial_weights(): Simulate Spatial Proximity and Adjacency Matrices

Built-in empirical and synthetic survey datasets

mys: mys: mean years of schooling people with disabilities.
mys_panel: mys_panel: mean years of schooling people with disabilities 2016 - 2026.
mys_proxmat: Example proximity matrix
cornsoybean: Corn and Soybean Survey and Satellite Data in 12 Iowa Counties
cornsoybeanmeans: Corn and Soybean Mean Number of Pixels per Segment for 12 Iowa Counties
sim_area: Multi-Distribution Synthetic Area-Level Dataset
sim_panel: Multi-Distribution Spatio-Temporal Panel Dataset