Package index • SUMMER

Child mortality estimation

getBirths(): Reformat full birth records into person-month format

getDirect(): Obtain the Horvitz-Thompson direct estimates and standard errors using delta method for a single survey.

getDirectList(): Obtain the Horvitz-Thompson direct estimates and standard errors using delta method for multiple surveys.

smoothDirect(): Smoothed direct estimates for mortality rates

smoothCluster(): Cluster-level space-time smoothing models for mortality rates

getSmoothed(): Extract smoothed estimates.

getAdjusted(): Adjust direct estimates and their associated variances

getDiag(): Extract posterior summaries of random effects

aggregateSurvey(): Aggregate estimators from different surveys.

Benchmark() experimental: Benchmark posterior draws to national estimates

print(<SUMMERmodel>): Print method for the smoothing models.

summary(<SUMMERmodel>): Summary method for the smoothing models.

print(<SUMMERprojlist>): Print method for the combined projection output.

summary(<SUMMERprojlist>): Summary method for the combined projection output. This function is the print method for class SUMMERprojlist.

General SAE models

smoothSurvey(): Fit space-time smoothing models for a binary outcome from complex surveys.

smoothArea(): Small area estimation via basic area level model

smoothUnit(): Smooth via basic unit level model

print(<SUMMERmodel.svy>): Print method for the smoothing models from smoothSurvey.

summary(<SUMMERmodel.svy>): Summary method for the smoothing model and output from smoothSurvey.

Visualization

mapPlot(): Plot region-level variables on a map

ridgePlot(): Calculate and plot posterior densities of the projected estimates

hatchPlot(): Plot maps with uncertainty hatching.

plot(<SUMMERproj>): Plot projection output.

tcpPlot(): Discrete-color maps based on the True Classification Probabilities

compareEstimates(): Plot heatmap comparing pairwise posterior exceedence probabilities for svysae object

mapEstimates(): Mapping estimates for svysae object

Utility functions

mapPoints(): Map GPS points to polygon regions

getAmat(): Extract adjacency matrix from the map

getCounts(): Aggregate person-month data into counts and totals by groups.

changeRegion(): Map region names to a common set.

expit(): Expit transformation

logit(): Logit transformation

rst(): Simulate spatial and temporal random effects

Pixel-level population simulation

getAreaName() experimental: Determines which administrative areas contain the given points

pixelPopToArea() areaPopToArea(): Aggregate populations to the specified areal level

simPopSPDE() simPopCustom(): Simulate populations and areal prevalences

aggPixelPreds(): Helper function of pixelPopToArea

poppRegionFromPopMat() experimental: Generate a population frame of a similar format to poppa argument of simPopCustom with a custom set of regions

simSPDE(): Simulate from the SPDE spatial model

getExpectedNperEA() getSortIndices() rStratifiedMultnomial() rStratifiedMultnomialBySubarea() rMyMultinomial() rMyMultinomialSubarea() rmultinom1() sampleNMultilevelMultinomial() sampleNMultilevelMultinomialFixed(): Internal functions for population simulation

makePopIntegrationTab() getPoppsub() adjustPopMat() experimental: Generating pixellated populations, and population frames

calibrateByRegion(): Calibrate the point level totals so their sum matches the regional totals

setThresholdsByRegion()

projKenya() experimental: Map projection for Kenya

Dataset

BRFSS: The BRFSS dataset

DemoData: Simulated child mortality person-month dataset.

DemoData2: Simulated dataset for prevalence mapping.

DemoMap: Uganda Admin-1 region map for illustration purpose

DemoMap2: Kenya Admin-1 region map for illustration purpose

KingCounty: Map of King County

MalawiData: Auxiliary data for Malawi 2000, 2004, 2010, and 2015 DHS.

MalawiMap: Malawi Admin-2 map

KenData: Auxiliary data for Kenya 2014 DHS.

kenyaPopulationData easpaKenyaNeonatal poppaKenya poppsubKenya: Kenya 2009 Census Frame and Related Datasets

Internal functions

rw.new(): New random walk 1 and 2 models for m-year to period random effects

rw.new.pc(): New random walk 1 and 2 models for m-year to period random effects

st.new(): New Type I to IV space time interaction models for m-year to period random effects

st.new.pc(): New Type I to IV space time interaction models for m-year to period random effects

iid.new(): New random IID models for m-year to period random effects

iid.new.pc(): New random IID models for m-year to period random effects

logitNormMean(): Calculate the mean of a distribution whose logit is Gaussian

simhyper(): Simulate hyperpriors from an GMRF

SUMMER-package SUMMER: SUMMER: Small-Area-Estimation Unit/Area Models and Methods for Estimation in R