extend documentiont hhTables and persTables for calibPop and fix some…

… roxygen warnings

DESCRIPTION

@@ -102,5 +102,5 @@ Collate:
     'whipple.R'
     'dataSets.R'
     'zzz.R'
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 Encoding: UTF-8

NAMESPACE

@@ -1,5 +1,7 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(as.array,spTable)
+S3method(as.table,spTable)
 S3method(calibVars,data.frame)
 S3method(calibVars,default)
 S3method(calibVars,matrix)
@@ -14,12 +16,17 @@ S3method(covWt,data.frame)
 S3method(covWt,dataObj)
 S3method(covWt,default)
 S3method(covWt,matrix)
+S3method(getExclude,data.frame)
+S3method(getExclude,data.table)
+S3method(getExclude,default)
 S3method(meanWt,dataObj)
 S3method(meanWt,default)
+S3method(plot,spTable)
 S3method(prepBwplotStats,data.frame)
 S3method(prepBwplotStats,default)
 S3method(prepCdf,data.frame)
 S3method(prepCdf,default)
+S3method(print,spTable)
 S3method(quantileWt,dataObj)
 S3method(quantileWt,default)
 S3method(varWt,dataObj)
@@ -50,6 +57,7 @@ export(getCat)
 export(getCdf)
 export(getCitizenship)
 export(getEcoStat)
+export(getExclude)
 export(getGender)
 export(getHsize)
 export(ipu)

R/calibPop.R

@@ -296,8 +296,10 @@ multiply_data <- function(data0,params,redist.var,split){
 #' @param observe.break When objective value has been saved \code{observe.times}-times the coefficient of variation is calculated over saved values; if the coefficient of variation falls below \code{observe.break}
 #' simmulated annealing terminates. This repeats for each new set of \code{observe.times} new values of the objecive function. Can help save run time if objective value does not improve much. Disable this termination by either setting \code{observe.times=0} or \code{observe.break=0}.
 #' @param n.forceCooldown integer, if the solution does not move for \code{n.forceCooldown} iterations then a cooldown is automatically done.
-#' @param hhTables information on population margins for households
-#' @param persTables information on population margins for persons
+#' @param hhTables Information on population margins for households. Can bei either a single \code{data.table} or \code{data.frame} or a list with multiple \code{data.tables}s or \code{data.frame}s.
+#' Each table must have one column named \code{Freq} and all other columns holding variable(s) of the synthetic population. Each row in this table corresponds to a the frequency count a one of the variable combination in that table, see examples.
+#' @param persTables Information on population margins for persons. Can bei either a single \code{data.table} or \code{data.frame} or a list with multiple \code{data.tables}s or \code{data.frame}s.
+#' Each table must have one column named \code{Freq} and all other columns holding variable(s) of the synthetic population. Each row in this table corresponds to a the frequency count a one of the variable combination in that table, see examples.
 #' @param redist.var single column in the population which can be redistributed in each `split`. Still experimental!
 #' @param redist.var.factor numeric in the interval (0,1]. Used in combinationo with `redist.var`, still experimental!
 #' @return Returns an object of class \code{\linkS4class{simPopObj}} with an

R/simPop-package.R

@@ -50,7 +50,6 @@
 #'
 #' @name simPop-package
 #' @aliases simPop-package simPop
-#' @docType package
 #' @author Bernhard Meindl, Matthias Templ, Andreas Alfons, Alexander Kowarik,
 #' 
 #' Maintainer: Matthias Templ <matthias.templ@@gmail.com>
@@ -68,6 +67,7 @@
 #' \emph{Privacy in Statistical Databases}, \strong{6344} of Lecture Notes in Computer Science, 174--186. Springer Verlag, Heidelberg. \doi{10.1007/978-3-642-15838-4_16}
 #' 
 #' @keywords package
+#' 
 #' @examples
 #'
 #' ## we use synthetic eusilcS survey sample data 
@@ -99,4 +99,5 @@
 #' ## using different methods, calibrating surveys or populations, etc. 
 #' ## -- see Templ et al. (2017) for more details.
 #' 
+"_PACKAGE"
 NULL

R/spTable.R

@@ -69,6 +69,7 @@ spTable <- function(inp, select) {
 }
 
 # methods for class "spTable"
+#' @export
 as.array.spTable <- function(x, ...) {
   values <- c(as.integer(x$expected), as.integer(x$realized))
   d <- c(dim(x$expected), 2)
@@ -77,14 +78,17 @@ as.array.spTable <- function(x, ...) {
   array(values, dim=d, dimnames=dn)
 }
 
+#' @export
 as.table.spTable <- function(x, ...) {
   tab <- as.array(x)
   class(tab) <- "table"
   tab
 }
 
+#' @export
 plot.spTable <- function(x, ...) spMosaic(x, ...)
 
+#' @export
 print.spTable <- function(x, ...) {
   # expected (from sample)
   cat("Expected:\n")

R/utils.R

@@ -86,11 +86,15 @@ dropLevels <- function(x, select = names(x)) {
 
 
 ## get which observations contain NAs (and need to be excluded)
+#' @export
 getExclude <- function(x, ...) UseMethod("getExclude")
+#' @export
 getExclude.default <- function(x, ...) which(is.na(x))
+#' @export
 getExclude.data.frame <- function(x, ...) {
   unique(which(is.na(x), arr.ind=TRUE)[, 1])
 }
+#' @export
 getExclude.data.table <- function(x, ...) {
   unique(which(is.na(x), arr.ind=TRUE)[, 1])
 }