Bayesian Demographic Estimation and Forecasting

Documentation for package ‘demest’ version 0.0.0.3.1

DESCRIPTION file.

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A B C D E F G H I K L M N P Q R S T W Z

demest-package

Bayesian demographic estimation and forecasting.

-- A --

AgCertain	Specify aggregate values.
AgFun	Specify aggregate values.
Aggregate	Specify aggregate values.
AgLife	Specify aggregate values.
AgNormal	Specify aggregate values.
AgPoisson	Specify aggregate values.

-- B --

Binomial

Specify first two levels of hierarchical model.

-- C --

CMP	Specify first two levels of hierarchical model.
Components	Specify priors for the components in a Mix prior.
Components-class	An S4 class to specify the components of a Mix prior.
continueEstimation	Add extra iterations to burnin or output.
continueSimulation	Add extra iterations to simulation
Covariates	Specify covariates in a prior for a main effect or interaction.
Covariates-class	S4 class to specify the covariates term of a prior.

-- D --

Damp	Specify the amount of damping in a DLM prior.
Damp-class	S4 classes to specify damping terms in DLM priors.
DampKnown-class	S4 classes to specify damping terms in DLM priors.
DampUnknown-class	S4 classes to specify damping terms in DLM priors.
decomposition	Decompose a demographic array
decomposition-method	Decompose a demographic array
describePriors	Text decription of priors
dhalft	The half-t distribution.
Dispersion	Specify the prior for the dispersion parameter in a CMP model.
Dispersion-class	S4 class to specify prior for dispersion parameter in CMP model.
DLM	Specify a Dynamic Linear Model (DLM) prior.
DLMS	Short version of 'DLM' function for creating Dynamic Linear Model priors

-- E --

equivalentSample	Convert estimates from a complex survey into a form suitable for analysis with an area-level model
equivalentSample-method	Convert estimates from a complex survey into a form suitable for analysis with an area-level model
Error	Specify the error term in a prior for a main effect or interaction.
Error-class	S4 classes to specify error terms for priors.
ErrorNorm-class	S4 classes to specify error terms for priors.
ErrorRobust-class	S4 classes to specify error terms for priors.
estimateAccount	Estimate demographic account and models from multiple noisy datasets.
estimateCounts	Estimate counts and model from one or more noisy datasets.
estimateModel	Estimate model from single reliable dataset.
Exch	Specify an exchangeable prior.
ExchFixed	Specify a simple exchangeable prior.

-- F --

fetch	Extract estimates from model output.
fetchBoth	Extract combined results from estimation and prediction.
fetchCoverage	Obtain the coverage ratio for a dataset.
fetchFiniteSD	Finite-population standard deviations.
fetchMCMC	Create a list of objects for analysis with package "coda".
fetchSummary	Summarise estimation output.
FiniteSD-class	S4 class to hold finite-population standard deviations.
finiteY	Estimate or predict finite-population quantity 'y'.

-- G --

gelmanDiag

Obtain potential scale reduction factors (Rhats).

-- H --

HalfT	Specify a half-t distribution.
HalfT-class	An S4 class to specify a truncated half-_t_ distribution.
halft-distn	The half-t distribution.

-- I --

Initial	Specify the prior for the initial value of the trend term in a DLM prior.
Initial-class	An S4 class to specify a normal prior for a scalar parameter.

-- K --

Known

Specify a prior where the mean varies but is treated as known.

-- L --

Level	Specify the level term in a DLM prior.
Level-class	An S4 class to specify the level term in a DLM prior.
likelihood	Specify first two levels of hierarchical model.
listContents	List of output from estimate function.
LN2	Log-normal model with two levels

-- M --

metropolis	Extract information on Metropolis-Hastings updates.
Mix	Specify a Mix prior.
Model	Specify a model for a single demographic series or dataset.

-- N --

Norm	Specify a normal distribution.
Norm-class	An S4 class to specify a normal distribution.
Normal	Specify first two levels of hierarchical model.
NormalFixed	Specify a model based on a normal distribution with known means and standard deviations.

-- P --

parameters	Extract summaries of parameter estimates from a SummaryResults object.
phalft	The half-t distribution.
phalft,	The half-t distribution.
plotHalfT	Plot the half-t distribution.
Poisson	Specify first two levels of hierarchical model.
PoissonBinomial	Specify a model based on a Poisson-binomial mixture.
predictAccount	Use results from function estimateAccount to make predictions.
predictCounts	Use results from function estimateCounts to make predictions.
predictModel	Use results from function estimateModel to make predictions.

-- Q --

qhalft	The half-t distribution.
qhalft,	The half-t distribution.

-- R --

rhalft	The half-t distribution.
rhalft,	The half-t distribution.
Round3	Specify a data model for random rounding to base 3.

-- S --

Season	Specify a seasonal effect in a DLM prior.
Season-class	An S4 class to specify a seasonal effect in a DLM prior.
show-method	S4 class to hold finite-population standard deviations.
show-method	S4 class summarizing results from estimation or prediction.
show-method	Print description of model or prior.
show-methods	Print description of model or prior.
showModel	Show final model specification.
simulateAccount	Create a synthetic demographic account
simulateModel	Draw parameters and data from a statistical model
SpecAgCertain-class	S4 classes to represent aggregate values.
SpecAgFun-class	S4 classes to represent aggregate values.
SpecAggregate-class	S4 classes to represent aggregate values.
SpecAgLife-class	S4 classes to represent aggregate values.
SpecAgNormal-class	S4 classes to represent aggregate values.
SpecAgPoisson-class	S4 classes to represent aggregate values.
SpecAgUncertain-class	S4 classes to represent aggregate values.
SpecBinomialVarying-class	S4 classes to specify a model.
SpecCMPVarying-class	S4 classes to specify a model.
SpecDLM-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMNoTrendNormCovNoSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMNoTrendNormCovWithSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMNoTrendNormZeroNoSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMNoTrendNormZeroWithSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMNoTrendRobustCovNoSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMNoTrendRobustCovWithSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMNoTrendRobustZeroNoSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMNoTrendRobustZeroWithSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMWithTrendNormCovNoSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMWithTrendNormCovWithSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMWithTrendNormZeroNoSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMWithTrendNormZeroWithSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMWithTrendRobustCovNoSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMWithTrendRobustCovWithSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMWithTrendRobustZeroNoSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecDLMWithTrendRobustZeroWithSeason-class	An S4 class to specify a dynamic linear model (DLM) prior.
SpecExch-class	A S4 class to specify an exchangeable prior.
SpecExchFixed-class	A S4 class to specify a simple exchangeable prior.
SpecExchNormCov-class	A S4 class to specify an exchangeable prior.
SpecExchNormZero-class	A S4 class to specify an exchangeable prior.
SpecExchRobustCov-class	A S4 class to specify an exchangeable prior.
SpecExchRobustZero-class	A S4 class to specify an exchangeable prior.
SpecKnown-class	A S4 class to specify a Known prior.
SpecKnownCertain-class	A S4 class to specify a Known prior.
SpecKnownUncertain-class	A S4 class to specify a Known prior.
SpecLikelihood-class	S4 classes to specify one or two levels of a model.
SpecLikelihoodBinomial-class	S4 classes to specify one or two levels of a model.
SpecLikelihoodCMP-class	S4 classes to specify one or two levels of a model.
SpecLikelihoodLN2-class	S4 classes to specify one or two levels of a model.
SpecLikelihoodNormalFixed-class	S4 classes to specify one or two levels of a model.
SpecLikelihoodNormalVarsigmaKnown-class	S4 classes to specify one or two levels of a model.
SpecLikelihoodNormalVarsigmaUnknown-class	S4 classes to specify one or two levels of a model.
SpecLikelihoodPoisson-class	S4 classes to specify one or two levels of a model.
SpecLikelihoodPoissonBinomialMixture-class	S4 classes to specify one or two levels of a model.
SpecLikelihoodRound3-class	S4 classes to specify one or two levels of a model.
SpecLikelihoodTFixed-class	S4 classes to specify one or two levels of a model.
SpecLN2-class	S4 classes to specify a model.
SpecMix-class	An S4 class to specify a Mix prior.
SpecModel-class	S4 classes to specify a model.
SpecNormalFixed-class	S4 classes to specify a model.
SpecNormalVaryingVarsigmaKnown-class	S4 classes to specify a model.
SpecNormalVaryingVarsigmaUnknown-class	S4 classes to specify a model.
SpecPoissonBinomialMixture-class	S4 classes to specify a model.
SpecPoissonVarying-class	S4 classes to specify a model.
SpecPrior-class	A S4 superclass for prior specifications.
SpecRound3-class	S4 classes to specify a model.
SpecTFixed-class	S4 classes to specify a model.
SpecZero-class	An S4 class to specify a Zero prior.
SummaryResults-class	S4 class summarizing results from estimation or prediction.

-- T --

TDist	Specify a vector of independent t-distributed variables
TDist-class	An S4 class to hold a vector of independent t-distributed variables
TFixed	Specify a model based on a Student's t distribution with known location, scale, and degrees of freedom.
Trend	Specify the trend term in a DLM prior.
Trend-class	An S4 class to specify the trend term in a DLM prior.

-- W --

Weights	Specify priors for the weights in a Mix prior.
Weights-class	An object of class 'Weights' is used to specify the trend term in a 'Mix' prior.

-- Z --

Zero	Specify a prior that sets all terms to zero.