add smooth = FALSE option for smoothSurvey()

DESCRIPTION

@@ -23,7 +23,7 @@ License: GPL (>= 2)
 Imports: survey, stats, spdep, survival, ggplot2, scales, utils, Matrix, reshape2, viridis, sp, sf, shadowtext, ggridges, methods, data.table, RColorBrewer, grDevices
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.2.1
+RoxygenNote: 7.2.3
 Additional_repositories: https://inla.r-inla-download.org/R/testing/
 Suggests: INLA, knitr, rmarkdown, readstata13, patchwork, rdhs, R.rsp, fields, sae, dplyr, tidyr
 VignetteBuilder: R.rsp, knitr

R/fitspace.R

@@ -40,6 +40,7 @@
 #' @param weight.strata a data frame with one column corresponding to \code{regionVar}, and columns specifying proportion of each strata for each region. This argument specifies the weights for strata-specific estimates. This is only used for the unit-level model. 
 #' @param nsim number of posterior draws to take. This is only used for the unit-level model when \code{weight.strata} is provided. 
 #' @param save.draws logical indicator of whether to save the full posterior draws.
+#' @param smooth logical indicator of whether to perform smoothing. If set to FALSE, a data frame of direct estimate is returned. Only used when \code{is.unit.level} is FALSE.
 #' @param ... additional arguments passed to \code{svydesign} function.
 #' 
 #' 
@@ -68,6 +69,13 @@
 #' clusterVar = "~clustid+id", CI = 0.95)
 #' summary(fit0)
 #' 
+#' # if only direct estimates without smoothing is of interest
+#' fit0.dir <- smoothSurvey(data=DemoData2, 
+#' Amat=DemoMap2$Amat, responseType="binary", 
+#' responseVar="tobacco.use", strataVar="strata", 
+#' weightVar="weights", regionVar="region", 
+#' clusterVar = "~clustid+id", CI = 0.95, smooth = FALSE)
+#' 
 #' # posterior draws can be returned with save.draws = TRUE
 #' fit0.draws <- smoothSurvey(data=DemoData2, 
 #' Amat=DemoMap2$Amat, responseType="binary", 
@@ -257,7 +265,7 @@
 #' @export
 
 
-smoothSurvey <- function(data, geo = NULL, Amat = NULL, X = NULL, X.unit = NULL, responseType = c("binary", "gaussian")[1], responseVar, strataVar="strata", weightVar="weights", regionVar="region", clusterVar = "~v001+v002", pc.u = 1, pc.alpha = 0.01, pc.u.phi = 0.5, pc.alpha.phi = 2/3, CI = 0.95, formula = NULL, timeVar = NULL, time.model = c("rw1", "rw2")[1], include_time_unstruct = FALSE, type.st = 1, direct.est = NULL, direct.est.var = NULL, is.unit.level = FALSE, is.agg = FALSE, strataVar.within = NULL, totalVar = NULL, weight.strata = NULL, nsim = 1000, save.draws = FALSE, ...){
+smoothSurvey <- function(data, geo = NULL, Amat = NULL, X = NULL, X.unit = NULL, responseType = c("binary", "gaussian")[1], responseVar, strataVar="strata", weightVar="weights", regionVar="region", clusterVar = "~v001+v002", pc.u = 1, pc.alpha = 0.01, pc.u.phi = 0.5, pc.alpha.phi = 2/3, CI = 0.95, formula = NULL, timeVar = NULL, time.model = c("rw1", "rw2")[1], include_time_unstruct = FALSE, type.st = 1, direct.est = NULL, direct.est.var = NULL, is.unit.level = FALSE, is.agg = FALSE, strataVar.within = NULL, totalVar = NULL, weight.strata = NULL, nsim = 1000, save.draws = FALSE, smooth = TRUE, ...){
 
  svy <- TRUE
  if(is.null(responseVar)){
@@ -590,7 +598,6 @@ smoothSurvey <- function(data, geo = NULL, Amat = NULL, X = NULL, X.unit = NULL,
  dat$region.unstruct <- dat$region.struct <- dat$region.int <- match(dat$region, rownames(Amat))
  if(!is.unit.level) dat$HT.logit.est[is.infinite(abs(dat$HT.logit.est))] <- NA 
 
-
  if(!is.null(timeVar)){
  dat <- dat[order(dat[, "time.struct"], dat[, "region.struct"]), ]
  }else{
@@ -685,6 +692,7 @@ smoothSurvey <- function(data, geo = NULL, Amat = NULL, X = NULL, X.unit = NULL,
  formula <- as.formula(paste(formulatext, formula, sep = "+"))
  } 
 
+ if(smooth){
  if(is.unit.level && responseType == "binary"){
  fit <- INLA::inla(formula, family="betabinomial", Ntrials=dat$total, control.compute = list(dic = T, mlik = T, cpo = T, config = TRUE, return.marginals.predictor=TRUE), data = dat, control.predictor = list(compute = TRUE), lincomb = NULL, quantiles = c((1-CI)/2, 0.5, 1-(1-CI)/2)) 
 
@@ -699,8 +707,9 @@ smoothSurvey <- function(data, geo = NULL, Amat = NULL, X = NULL, X.unit = NULL,
  }else{
  fit <- INLA::inla(formula, family = "gaussian", control.compute = list(dic = T, mlik = T, cpo = T, config = save.draws, return.marginals.predictor=TRUE), data = dat, control.predictor = list(compute = TRUE), control.family = list(hyper= list(prec = list(initial= log(1), fixed= TRUE))), scale = dat$HT.logit.prec, lincomb = NULL, quantiles = c((1-CI)/2, 0.5, 1-(1-CI)/2)) 
  }
-
-
+ }else{
+ fit <- NULL
+ }
 
  n <- max(dat$region.struct) 
  temp <- NA
@@ -719,7 +728,7 @@ smoothSurvey <- function(data, geo = NULL, Amat = NULL, X = NULL, X.unit = NULL,
  }
 
 
-
+  if(smooth){
  for(i in 1:dim(proj)[1]){
  if(!is.unit.level){
  tmp <- matrix(INLA::inla.rmarginal(1e5, fit$marginals.linear.predictor[[i]]))
@@ -838,6 +847,9 @@ smoothSurvey <- function(data, geo = NULL, Amat = NULL, X = NULL, X.unit = NULL,
  }else{
  proj.agg <- NULL
  }
+ }else{
+ proj.agg <- NULL
+ }
 
  if(!is.unit.level){
  # organize output nicer