smoothArea: Smooth via area level model

Description

Generates small area estimates by smoothing direct estimates using an area level model

Usage

smoothArea(
  formula,
  domain,
  design = NULL,
  responseType = c("gaussian", "binary")[1],
  Amat = NULL,
  direct.est = NULL,
  X.area = NULL,
  domain.size = NULL,
  pc.u = 1,
  pc.alpha = 0.01,
  pc.u.phi = 0.5,
  pc.alpha.phi = 2/3,
  CI = 0.95,
  n.sample = 250,
  var.tol = 1e-10
)

Value

A list with elements

direct.est: direct estimates
s.dir.iid.fit: fitted INLA object for iid domain effects model
s.dir.iid.est: non-spatial smoothed estimates
s.dir.sp.fit: fitted INLA object for spatial domain effects model
s.dir.sp.est: spatially smoothed estimates (if adjacency matrix provided)

Arguments

formula: an object of class 'formula' describing the model to be fitted. If direct.est is specified, the right hand side of the formula is not necessary.
domain: formula specifying variable containing domain labels
design: an object of class "svydesign" containing the data for the model
responseType: of the response variable, currently supports 'binary' (default with logit link function) or 'gaussian'.
Amat: adjacency matrix for the regions. If set to NULL, the IID spatial effect will be used.
direct.est: data frame of direct estimates, with first column containing domain, second column containing direct estimate, and third column containing variance of direct estimate.
X.area: areal covariates data frame. One of the column names needs to match 'domain', in order to be linked to the data input. Currently only supporting time-invariant domain-level covariates.
domain.size: domain size data frame. One of the column names needs to match 'domain' in order to be linked to the data input and there must be a size column containing domain sizes.
pc.u: hyperparameter U for the PC prior on precisions.
pc.alpha: hyperparameter alpha for the PC prior on precisions.
pc.u.phi: hyperparameter U for the PC prior on the mixture probability phi in BYM2 model.
pc.alpha.phi: hyperparameter alpha for the PC prior on the mixture probability phi in BYM2 model.
CI: the desired posterior credible interval to calculate
n.sample: number of draws from posterior used to compute summaries
var.tol: tolerance parameter; if variance of an area's direct estimator is below this value, that direct estimator is dropped from model