diff --git a/NAMESPACE b/NAMESPACE
index d4a106c3..786c9aad 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -5,6 +5,7 @@ export(AddGearGroupStoxBiotic)
 export(AddGearGroupStoxLanding)
 export(AddPeriodStoxBiotic)
 export(AddPeriodStoxLanding)
+export(AddPsuStratificationVariables)
 export(AddStratumStoxBiotic)
 export(AddStratumStoxLanding)
 export(AnalyticalPSUEstimate)
diff --git a/NEWS.md b/NEWS.md
index 5a19b4d0..5aef5989 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,4 +1,6 @@
 # 1.5.0-9003
+* Added function for annotating stratification variables to sampling parameters (AddPsuStratificationVariables) (#163)
+* Added option for computing sampling parameters for Proportion Poisson Sampling from data records (option DefinitionMethod='ProportionalPoissonSampling' to ComputePSUSamplingParameters) (#165)
 * Added functions for sampling frame expansion (ExtendAnalyticalSamplingFrameCoverage), and domain interpolation (InterpolateAnalyticalDomainEstimates) (#154)
 * Changed how Stratification variables and Domain variables are matched to landings with AnalyticalRatioEstimate (# 125)
 * Replaced DefinePSUSamplingParameters (processdata) with ComputePSUSamplingParameters (no processdata) and ReadPSUSamplingParameters (no processdata). This change breaks some pre-release projects (v. v1.3-9006). (#127)
diff --git a/R/StoxAnalyticalAnalysisFunctions.R b/R/StoxAnalyticalAnalysisFunctions.R
deleted file mode 100644
index 6169a515..00000000
--- a/R/StoxAnalyticalAnalysisFunctions.R
+++ /dev/null
@@ -1,3 +0,0 @@
-#' @noRd
-PrepareHorvitzThompsonDomainEstimate <- function(){}
-
diff --git a/R/StoxAnalyticalBaselineFunctions.R b/R/StoxAnalyticalBaselineFunctions.R
index 1ea1b791..4eca04ee 100644
--- a/R/StoxAnalyticalBaselineFunctions.R
+++ b/R/StoxAnalyticalBaselineFunctions.R
@@ -161,6 +161,53 @@ ReadPSUSamplingParameters <- function(FileName){
   return(parseDesignParameters(FileName))
 }
 
+#' @noRd
+computePpsParametersStoxBiotic <- function(StoxBioticData, SamplingUnitId, Quota, StratumName, ExpectedSampleSize){
+  
+  checkMandatory(StoxBioticData, "StoxBioticData")
+  checkMandatory(SamplingUnitId, "SamplingUnitId")
+  checkMandatory(Quota, "Quota")
+  checkMandatory(StratumName, "StratumName")
+  checkMandatory(ExpectedSampleSize, "ExpectedSampleSize")
+  
+  if (length(unique(StoxBioticData$SpeciesCategory$SpeciesCategory))!=1){
+    stop(paste("The DefinitionMethod 'ProportionalPoissonSampling', requires only one species category to be present in sample records. Found:", 
+               truncateStringVector(unique(StoxBioticData$SpeciesCategory$SpeciesCategory))))
+  }
+  
+  if (!(SamplingUnitId %in% names(StoxBioticData$Haul))){
+    stop(paste("The argument 'SamplingUnitId' must identify a variable in the 'Haul'-table of 'StoxBioticData"))
+  }
+  
+  if (any(is.na(StoxBioticData$Sample$CatchFractionWeight))){
+    missing <- StoxBioticData$Sample$Sample[is.na(StoxBioticData$Sample$CatchFractionWeight)]
+    stop(paste("Cannot computed sampling parameters with missing catch weights, missing for samples: ", truncateStringVector(missing)))
+  }
+  n <- ExpectedSampleSize
+  
+  flatBiotic <- RstoxData::mergeByStoxKeys(StoxBioticData$Haul, StoxBioticData$Sample, StoxDataType = "StoxBiotic")
+  SelectionTable <- flatBiotic[,list(catchWeight=sum(get("CatchFractionWeight"))), by=list(SamplingUnitId=get(SamplingUnitId))]
+  SelectionTable$SelectionProbability <- SelectionTable$catchWeight / Quota
+  SelectionTable$HHsamplingWeight <- 1 / (SelectionTable$SelectionProbability * sum(1/SelectionTable$SelectionProbability))
+  SelectionTable$InclusionProbability <- 1-((1-SelectionTable$SelectionProbability)**n)
+  SelectionTable$HTsamplingWeight <- 1 / (SelectionTable$InclusionProbability * sum(1/SelectionTable$InclusionProbability))
+  SelectionTable$Order <- as.numeric(NA)
+  SelectionTable$Stratum <- StratumName
+  SelectionTable$SelectionDescription <- ""
+  SelectionTable <- SelectionTable[,.SD,.SDcol=c("Stratum", "Order", "SamplingUnitId", "InclusionProbability", "HTsamplingWeight", "SelectionProbability", "HHsamplingWeight", "SelectionDescription")]
+  
+  SampleTable <- data.table::data.table(Stratum=StratumName, N=as.numeric(NA), n=n, SelectionMethod="Poisson", FrameDescription="")
+  
+  StratificationVariables <- data.table::data.table(Stratum=StratumName)
+
+  samplingParams <- list()
+  samplingParams$SampleTable <- SampleTable
+  samplingParams$SelectionTable <- SelectionTable
+  samplingParams$StratificationVariables <- StratificationVariables
+    
+  return(samplingParams)
+}
+
 #' Compute PSU Sampling Design Parameters
 #' @description 
 #'  Compute sampling parameters for Primary Sampling Units in multi-stage sampling.
@@ -172,27 +219,152 @@ ReadPSUSamplingParameters <- function(FileName){
 #'  This is a reasonable approximation if within-strata sampling is approximately simple random selections,
 #'  the sample intensitiy is low (only a small fraction of the population is sampled),
 #'  and non-response is believed to be random.
-#' @param DefinitionMethod 'AdHocStoxBiotic'
+#'  
+#'  If 'DefinitionMethod' is 'ProportionalPoissonSampling', Unstratified (singe stratum) Poission sampling with selection probabilities
+#'  proportional to catch size is assumed. 'SamplingUnitId' must be a variable on the Haul table of 'StoxBioticData' for this option,
+#'  and the data must contain only one species (SpeciesCategory in 'StoxBioticData'). SelectionProbabilities are assigned
+#'  based on the total catch of the species in each haul. Specifically, for a haul \eqn{i}; selectionprobabilites, \eqn{p_{i}} and inclusionprobabilities \eqn{\pi_{i}}
+#'  are calculated as:
+#'  
+#'  \deqn{p_{i}=\frac{w_{i}}{W}}
+#'  
+#'  \deqn{\pi_{i}=1-(1-p_{i})^{n}}
+#'  
+#'  where:
+#'  \itemize{ 
+#'    \item \eqn{w_{i}} is the sum of all catch weights in haul \eqn{i} ('CatchFractionWeight' on the 'Sample' table of 'StoxBioticData') 
+#'    \item \eqn{W} is the expected total catch in the fishery (argument 'Quota')
+#'    \item \eqn{n} is the expected sample size (argument 'ExpectedSampleSize')
+#'  }
+#'  If proportional poisson sampling was actually used to select the sampled records in 'StoxBioticData',
+#'  sampling parameters would have been obtained prior to sampling, and it is generally preferable to obtain these, 
+#'  and import those via \code{\link[RstoxFDA]{ReadPSUSamplingParameters}}. Weight-records are sometimes corrected after
+#'  sampling parameters are calculated, and proper information about non-response can not be recalculated after the fact.
+#'  
+#'  Proportional poisson sampling also allows the sampler to combine rigour and pragmatism, by varying sampling parameters
+#'  in the course of sample selection. For instance 'n' may be changed during the sampling period, if non-response 
+#'  turns out to be higher than expected. Such flexibilities are not
+#'  provided by this function, and the approximation may be severely compromised, if such pragmatism is not accounted for.
+#'  
+#' @param DefinitionMethod 'AdHocStoxBiotic' or 'ProportionalPoissonSampling'
 #' @param StoxBioticData \code{\link[RstoxData]{StoxBioticData}} Sample data to construct design parameters from
 #' @param SamplingUnitId name of column in 'StoxBioticData' that identifies the Primary Sampling Unit the design is constructed for.
-#' @param StratificationColumns name of any column (at the same table as 'SamplingUnitId') that are to be used to define Strata for sampling.
+#' @param StratificationColumns name of any column (at the same table as 'SamplingUnitId') that are to be used to define Strata for sampling. (for DefinitionMethod 'AdHocStoxBiotic')
+#' @param StratumName name of the stratum sampling parameters are calculated for (for DefinitionMethod 'ProportionalPoissonSampling')
+#' @param Quota expected total catch in sampling frame in kg (for DefinitionMethod 'ProportionalPoissonSampling')
+#' @param ExpectedSampleSize the expected sample size for Possion sampling (for DefinitionMethod 'ProportionalPoissonSampling')
 #' @return \code{\link[RstoxFDA]{PSUSamplingParametersData}}
 #' @examples
-#'  # parameters for simpler random haul-selection, stratified by GearGroup
+#'  # parameters for simple random haul-selection, stratified by GearGroup
 #'  PSUparams <- ComputePSUSamplingParameters(RstoxFDA::StoxBioticDataExample, 
 #'   "AdHocStoxBiotic", 
 #'   "Haul", 
 #'   "GearGroup")
+#'   
+#'  # parameters for haul selection proportional to catch size.
+#'  calculatedPps <- RstoxFDA::ComputePSUSamplingParameters(RstoxFDA::CatchLotteryExample, 
+#'     "ProportionalPoissonSampling", 
+#'     "serialnumber", StratumName = 
+#'     "Nordsjo", Quota = 124*1e6, 
+#'     ExpectedSampleSize = 110)
 #' 
 #' @export
 #' @concept StoX-functions
 #' @concept Analytical estimation
 #' @md
-ComputePSUSamplingParameters <- function(StoxBioticData, DefinitionMethod=c("AdHocStoxBiotic"), SamplingUnitId=character(), StratificationColumns=character()){
+ComputePSUSamplingParameters <- function(StoxBioticData, DefinitionMethod=c("AdHocStoxBiotic", "ProportionalPoissonSampling"), SamplingUnitId=character(), StratificationColumns=character(), StratumName=character(), Quota=numeric(), ExpectedSampleSize=numeric()){
+
+  DefinitionMethod <- checkOptions(DefinitionMethod, "DefinitionMethod", c("AdHocStoxBiotic", "ProportionalPoissonSampling"))
 
-  DefinitionMethod <- checkOptions(DefinitionMethod, "DefinitionMethod", c("AdHocStoxBiotic"))
+  if (DefinitionMethod=="AdHocStoxBiotic"){
+    return(assumeDesignParametersStoxBiotic(StoxBioticData, SamplingUnitId, StratificationColumns))    
+  }
+  else if (DefinitionMethod=="ProportionalPoissonSampling"){
+    return(computePpsParametersStoxBiotic(StoxBioticData, SamplingUnitId, Quota, StratumName, ExpectedSampleSize))    
+  }
+  else{
+    stop(paste("The option", DefinitionMethod, "is not recognized for the argument 'DefinitionMethod'"))
+  }
+
+}
+
+is.StratificationVariablesData <- function(StratificationVariablesTable){
+  if(!data.table::is.data.table(StratificationVariablesTable)){
+    return(FALSE)
+  }
+  if (!("Stratum" %in% names(StratificationVariablesTable))){
+    return(FALSE)
+  }
+  return(TRUE)
+}
+
+#' Add Stratification columns to 'PSUSamplingParametersData'
+#' @description
+#'  Add additional variables to encode strata and its correspondance with census data (e.g. landings data).
+#' @details
+#'  \code{\link[RstoxFDA]{PSUSamplingParametersData}} provide sampling parameters by strata.
+#'  Optionally, it may also contain additional variables that encode the stratification in terms of variables
+#'  available in other data sources, such as \code{\link[RstoxData]{StoxLandingData}}. This function allows
+#'  such variables to be added, if not already present.
+#'  
+#'  More detailed encoding of stratification is useful for 
+#'  encoding the sampling frame of the design provided by 'PSUSamplingParametersData'. By encoding all strata
+#'  in terms of variables that are available in census-data, the correspondance between sampling frame and
+#'  target population can be encoded. This information will be available in downstream estimates (e.g.
+#'  \code{\link[RstoxFDA]{AnalyticalPopulationEstimate}}) and allow for pragmatic inference to
+#'  out-of-frame strata (via \code{\link[RstoxFDA]{ExtendAnalyticalSamplingFrameCoverage}}).
+#' 
+#' @param PSUSamplingParametersData Sampling parameters stratification variables should be added to
+#' @param StratificationVariables name of variables to add
+#' @param StratificationVariablesTable value-combinations for the variables to add to each stratum
+#' @return \code{\link[RstoxFDA]{PSUSamplingParametersData}}
+#' @export
+#' @concept StoX-functions
+#' @concept Analytical estimation
+#' @md
+AddPsuStratificationVariables <- function(PSUSamplingParametersData, StratificationVariables, StratificationVariablesTable=data.table::data.table()){
+  
+  checkMandatory(PSUSamplingParametersData, "PSUSamplingParametersData")
+  checkMandatory(StratificationVariables, "StratificationVariables")
+  checkMandatory(StratificationVariablesTable, "StratificationVariablesTable")
+  
+  if (length(names(PSUSamplingParametersData$StratificationVariables))>1){
+    stop("'PSUSamplingParametersData' already has StratificationVariables")
+  }
+  
+  if (!is.StratificationVariablesData(StratificationVariablesTable)){
+    stop("Invalid 'StratificationVariablesTable'.")
+  }
+  
+  if (!all(StratificationVariablesTable$Stratum %in% PSUSamplingParametersData$StratificationVariables$Stratum)){
+    missing <- StratificationVariablesTable$Stratum[!(StratificationVariablesTable$Stratum %in% PSUSamplingParametersData$StratificationVariables$Stratum)]
+    stop(paste("Not all strata in 'StratificationVariablesTable' exist in 'PSUSamplingParametersData'. Missing", truncateStringVector(missing)))
+  }
+  
+  if (!all(PSUSamplingParametersData$StratificationVariables$Stratum %in% StratificationVariablesTable$Stratum)){
+    missing <- PSUSamplingParametersData$StratificationVariables$Stratum[!(PSUSamplingParametersData$StratificationVariables$Stratum %in% StratificationVariablesTable$Stratum)]
+    stop(paste("Stratification variables are not provided for strata:", truncateStringVector(missing)))
+  }
+  
+  if (!all(StratificationVariables %in% names(StratificationVariablesTable))){
+    stop("Not all StratificationVariables are in the StratificationVariablesTable")
+  }
+  if (!all(names(StratificationVariablesTable) %in% c("Stratum", StratificationVariables))){
+    stop("Some StratificationVariables are not in the StratificationVariablesTable")
+  }
+  
+  stratCount <- StratificationVariablesTable[,list(strata=length(unique(get("Stratum")))), by=list(stratVarString=apply(StratificationVariablesTable[,.SD,.SDcol=names(StratificationVariablesTable)[names(StratificationVariablesTable) != "Stratum"]], 1, paste, collapse="/"))]
+  manyStrata <- stratCount[get("strata")>1,]
+  if (nrow(manyStrata)>0){
+    stop(paste("Stratification variables does not identify strata. Several strata overlap with:", truncateStringVector(manyStrata$stratVarString)))
+  }
+
+  PSUSamplingParametersData$StratificationVariables <- merge(PSUSamplingParametersData$StratificationVariables,
+                                                             StratificationVariablesTable,
+                                                             by="Stratum")
+  
+  return(PSUSamplingParametersData)
   
-  return(assumeDesignParametersStoxBiotic(StoxBioticData, SamplingUnitId, StratificationColumns))
 }
 
 #' collapse strata, recalulate n/N and sampling weights
@@ -859,6 +1031,7 @@ covarAbundance <- function(Totals, PSUSampling, MeanOfMeans){
 
       relPSUDomainSize <- sum(table$HHsamplingWeight[!duplicated(table$SamplingUnitId)])
       relDomainSizes <- table[,list(relDomainSize=sum(get("HHsamplingWeight")[!duplicated(get("SamplingUnitId"))])), by=c("Stratum", "Domain")]
+      
       stopifnot(relPSUDomainSize<=1+1e-1)
       stopifnot(all(relDomainSizes$relDomainSize <= relPSUDomainSize))
 
@@ -906,6 +1079,7 @@ covarVariables <- function(Totals, PSUSampling, MeanOfMeans, Abundance){
       
       relPSUDomainSize <- sum(table$HHsamplingWeight[!duplicated(table$SamplingUnitId)])
       relDomainSizes <- table[,list(relDomainSize=sum(get("HHsamplingWeight")[!duplicated(get("SamplingUnitId"))])), by=c("Stratum", "Domain")]
+      
       stopifnot(relPSUDomainSize<=1+1e-1)
       stopifnot(all(relDomainSizes$relDomainSize <= relPSUDomainSize))
       
@@ -1581,6 +1755,12 @@ AnalyticalRatioEstimate <- function(AnalyticalPopulationEstimateData, StoxLandin
 
 }
 
+#' 
+#' @noRd
+AggregateAnalyticalEstimate <- function(AnalyticalPopulationEstimateData, RetainStrata=character(), AggregateStratumName=character()){
+  # consider an option for combining with several 'AnalyticalPopulationEstimateData'
+}
+
 #' Fills in unsampled strata according to 'strict' after new domains and new strata has been inferred and added to the estimation object
 #' @noRd
 fillStrict <- function(extendedAnalyticalPopulationEstimateData){
@@ -2201,8 +2381,3 @@ InterpolateAnalyticalDomainEstimates <- function(AnalyticalPopulationEstimateDat
   }
     
 }
-
-#' @noRd
-ProbabilisticSuperIndividuals <- function(StoxBioticData, PSUSamplingParametersData, IndividualSamplingParametersData){
-  
-}
diff --git a/R/StoxDataTypes.R b/R/StoxDataTypes.R
index 6e4ef485..bcde6fac 100644
--- a/R/StoxDataTypes.R
+++ b/R/StoxDataTypes.R
@@ -2402,7 +2402,21 @@ stoxFunctionAttributes <- list(
       StratificationColumns = "stratificationcolumns"
       ),
     functionParameterDefaults = list(
-      DefinitionMethod = "AdHocStoxBiotic"
+      DefinitionMethod = "ProportionalPoissonSampling"
+    ),
+    functionArgumentHierarchy = list(
+      StratificationColumns = list(
+        DefinitionMethod = "AdHocStoxBiotic"
+      ),
+      StratumName = list(
+        DefinitionMethod = "ProportionalPoissonSampling"
+      ),
+      Quota = list(
+        DefinitionMethod = "ProportionalPoissonSampling"
+      ),
+      ExpectedSampleSize = list(
+        DefinitionMethod = "ProportionalPoissonSampling"
+      )
     )
     ),
   ReadPSUSamplingParameters = list(
@@ -2413,6 +2427,15 @@ stoxFunctionAttributes <- list(
       FileName = "filePath"
     )
   ),
+  AddPsuStratificationVariables = list(
+    functionType = "modelData", 
+    functionCategory = "baseline", 
+    functionOutputDataType = "PSUSamplingParametersData",
+    functionParameterFormat = list(
+      StratificationVariables = "stratificationvariablesvector",
+      StratificationVariablesTable = "stratificationvariablestable"
+    )
+  ),
   AssignPSUSamplingParameters = list(
     functionType = "modelData", 
     functionCategory = "baseline", 
@@ -3214,6 +3237,21 @@ processPropertyFormats <- list(
       return(pv)
     },
     variableTypes = "character"
+  ),
+  stratificationvariablesvector = list(
+    class = "vector",
+    title = "Names of stratification variables to add", 
+    variableTypes = "character"
+  ),
+  stratificationvariablestable = list(
+    class = "table", 
+    title = "Table of Stratification variables for each Stratum", 
+    columnNames = function(StratificationVariables) {
+      c("Stratum", StratificationVariables)
+    }, 
+    variableTypes = function(StratificationVariables) {
+      rep("character", 1 + length(StratificationVariables))
+    }
   )
 )
 
diff --git a/inst/extdata/functionArguments.rds b/inst/extdata/functionArguments.rds
index eae81ec8..6020bea0 100644
Binary files a/inst/extdata/functionArguments.rds and b/inst/extdata/functionArguments.rds differ
diff --git a/inst/tinytest/test-StoxAnalyticalBaselineFunctions.R b/inst/tinytest/test-StoxAnalyticalBaselineFunctions.R
index 46ac74e1..95a0d10b 100644
--- a/inst/tinytest/test-StoxAnalyticalBaselineFunctions.R
+++ b/inst/tinytest/test-StoxAnalyticalBaselineFunctions.R
@@ -33,7 +33,45 @@ expect_true(abs((sum(1/designParamsCorrected$SelectionTable$InclusionProbability
 #HH should be approximately the same after non-response correction
 expect_true(abs((mean(1/designParamsCorrected$SelectionTable$InclusionProbability)-mean(1/designParams$SelectionTable$InclusionProbability))/sum(1/designParamsCorrected$SelectionTable$InclusionProbability))<0.1)
 
-#define from data
+
+#define pps-parameters from data
+calculatedPps <- RstoxFDA::ComputePSUSamplingParameters(RstoxFDA::CatchLotteryExample, 
+                                                        "ProportionalPoissonSampling", 
+                                                        "serialnumber", StratumName = 
+                                                          "Nordsjo", Quota = 124*1e6, 
+                                                        ExpectedSampleSize = 110)
+expect_true(RstoxFDA:::is.PSUSamplingParametersData(calculatedPps))
+comp <- merge(calculatedPps$SelectionTable, 
+              RstoxFDA::CatchLotterySamplingExample$SelectionTable
+              , by=c("Stratum", "SamplingUnitId"))
+comp <- comp[!(comp$SamplingUnitId %in% c("38408", "38409"))] #remove catches that has had weights corrected or something
+expect_true(all(comp$SelectionProbability.x - comp$SelectionProbability.y < 1e-10))
+expect_true(all(comp$InclusionProbability.x - comp$InclusionProbability.y < 1e-10))
+
+# add stratification columns
+expect_error(RstoxFDA:::AddPsuStratificationVariables(calculatedPps, StratificationVariables = c("VesselLengthGroup", "VesselFlag"), StratificationVariablesTable = data.table::data.table(VesselLengthGroup="o15m", VesselFlag="NOR")), "Invalid 'StratificationVariablesTable'")
+expect_error(RstoxFDA:::AddPsuStratificationVariables(calculatedPps, StratificationVariables = c("VesselLengthGroup", "VesselFlag"), StratificationVariablesTable = data.table::data.table(Stratum=c("s1", "s2"), VesselLengthGroup=c("o15m","o15m"), VesselFlag=c("NOR","NOR"))), "Not all strata in 'StratificationVariablesTable' exist in 'PSUSamplingParametersData'.")
+calculatedPps2 <- calculatedPps
+calculatedPps2$StratificationVariables <- data.table::data.table(Stratum=c("s1","s2"))
+expect_error(RstoxFDA:::AddPsuStratificationVariables(calculatedPps2, StratificationVariables = c("VesselLengthGroup", "VesselFlag"), StratificationVariablesTable = data.table::data.table(Stratum=c("s1", "s2"), VesselLengthGroup=c("o15m","o15m"), VesselFlag=c("NOR","NOR"))), "Stratification variables does not identify strata. Several strata overlap with")
+
+calculatedPpsStrat <- RstoxFDA:::AddPsuStratificationVariables(calculatedPps, StratificationVariables = c("VesselFlag"), StratificationVariablesTable = data.table::data.table(Stratum="Nordsjo", VesselFlag="NOR"))
+expect_true(all(c("Stratum", "VesselFlag") %in% names(calculatedPpsStrat$StratificationVariables)))
+expect_equal(nrow(calculatedPpsStrat$StratificationVariables), 1)
+
+calculatedPpsStrat <- RstoxFDA:::AddPsuStratificationVariables(calculatedPps, StratificationVariables = c("VesselLengthGroup", "VesselFlag"), StratificationVariablesTable = data.table::data.table(Stratum="Nordsjo", VesselLengthGroup="o15m", VesselFlag="NOR"))
+expect_true(all(c("Stratum", "VesselLengthGroup", "VesselFlag") %in% names(calculatedPpsStrat$StratificationVariables)))
+expect_equal(nrow(calculatedPpsStrat$StratificationVariables), 1)
+
+calculatedPpsStrat <- RstoxFDA:::AddPsuStratificationVariables(calculatedPps, StratificationVariables = c("VesselLengthGroup", "VesselFlag"), StratificationVariablesTable = data.table::data.table(Stratum=c("Nordsjo", "Nordsjo"), VesselLengthGroup=c("u15m","o15m"), VesselFlag=c("NOR")))
+expect_true(all(c("Stratum", "VesselLengthGroup", "VesselFlag") %in% names(calculatedPpsStrat$StratificationVariables)))
+expect_equal(nrow(calculatedPpsStrat$StratificationVariables), 2)
+
+#sampling weights are different, because of the two removed hauls above, but should be proportional
+expect_true(length(unique(round(comp$HHsamplingWeight.x / comp$HHsamplingWeight.y, digits=10)))==1)
+expect_true(length(unique(round(comp$HTsamplingWeight.x / comp$HTsamplingWeight.y, digits=10)))==1)
+
+#define equal prob fixed-size selection from data
 suppressWarnings(StoxBioticData <- RstoxData::StoxBiotic(RstoxData::ReadBiotic(system.file("testresources", "biotic_v3_example.xml", package="RstoxFDA"))))
 designParamsSB <- RstoxFDA:::ComputePSUSamplingParameters(StoxBioticData=StoxBioticData, SamplingUnitId = "Individual", StratificationColumns = c("SpeciesCategoryKey"))
 expect_true(RstoxFDA:::is.PSUSamplingParametersData(designParamsSB))
@@ -123,7 +161,9 @@ weights <- lsCol$SelectionTable[,list(meanN=sum(HTsamplingWeight)), by=c("Stratu
 expect_true(all(abs(weights$meanN-1) < 1e-6))
 
 
-#test estimate with HansenHurwitzDomainEstimate
+
+
+#test estimate with HansenHurwitzDomainEstimate, read params
 data <- RstoxFDA::CatchLotteryExample
 indSampling <- RstoxFDA:::ComputeIndividualSamplingParameters(data, "SRS", c("IndividualAge"))
 
@@ -306,7 +346,15 @@ popEstPD <- RstoxFDA:::AnalyticalPopulationEstimate(stationDesign, psuEstPD)
 expect_true(abs(popEst$Abundance$Abundance - sum(popEstPD$Abundance$Abundance))/popEst$Abundance$Abundance < 1e-2)
 expect_true(abs(popEst$Variables$Total - sum(popEstPD$Variables$Total))/popEst$Variables$Total < 1e-2)
 
+#test PSU domains, computed PSU sampling parameters
+ex2 <- RstoxFDA::CatchLotteryExample
+ex2$SpeciesCategory$SpeciesCategory <- "061104"
+stationDesignComp <- RstoxFDA::ComputePSUSamplingParameters(StoxBioticData = ex2, "ProportionalPoissonSampling", "serialnumber", StratumName = "Nordsjo", Quota = 124*1e6, ExpectedSampleSize = 110)
+stationDesignComp <- RstoxFDA::AssignPSUSamplingParameters(stationDesignComp, ex2, "serialnumber", "Haul", "MissingAtRandom")
 
+psuEstCompPD <- RstoxFDA:::AnalyticalPSUEstimate(ex2, srs, c("IndividualRoundWeight"), c("IndividualAge"), c("Gear"))
+popEstCompPD <- RstoxFDA:::AnalyticalPopulationEstimate(stationDesignComp, psuEstCompPD)
+expect_true(abs(sum(popEstCompPD$Abundance$Abundance) - sum(popEstPD$Abundance$Abundance))/sum(popEstCompPD$Abundance$Abundance) < 1e-2)
 #
 # Test ratio estimation
 #
diff --git a/man/AddPsuStratificationVariables.Rd b/man/AddPsuStratificationVariables.Rd
new file mode 100644
index 00000000..4e095397
--- /dev/null
+++ b/man/AddPsuStratificationVariables.Rd
@@ -0,0 +1,40 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/StoxAnalyticalBaselineFunctions.R
+\name{AddPsuStratificationVariables}
+\alias{AddPsuStratificationVariables}
+\title{Add Stratification columns to 'PSUSamplingParametersData'}
+\usage{
+AddPsuStratificationVariables(
+  PSUSamplingParametersData,
+  StratificationVariables,
+  StratificationVariablesTable = data.table::data.table()
+)
+}
+\arguments{
+\item{PSUSamplingParametersData}{Sampling parameters stratification variables should be added to}
+
+\item{StratificationVariables}{name of variables to add}
+
+\item{StratificationVariablesTable}{value-combinations for the variables to add to each stratum}
+}
+\value{
+\code{\link[RstoxFDA]{PSUSamplingParametersData}}
+}
+\description{
+Add additional variables to encode strata and its correspondance with census data (e.g. landings data).
+}
+\details{
+\code{\link[RstoxFDA]{PSUSamplingParametersData}} provide sampling parameters by strata.
+Optionally, it may also contain additional variables that encode the stratification in terms of variables
+available in other data sources, such as \code{\link[RstoxData]{StoxLandingData}}. This function allows
+such variables to be added, if not already present.
+
+More detailed encoding of stratification is useful for
+encoding the sampling frame of the design provided by 'PSUSamplingParametersData'. By encoding all strata
+in terms of variables that are available in census-data, the correspondance between sampling frame and
+target population can be encoded. This information will be available in downstream estimates (e.g.
+\code{\link[RstoxFDA]{AnalyticalPopulationEstimate}}) and allow for pragmatic inference to
+out-of-frame strata (via \code{\link[RstoxFDA]{ExtendAnalyticalSamplingFrameCoverage}}).
+}
+\concept{Analytical estimation}
+\concept{StoX-functions}
diff --git a/man/ComputePSUSamplingParameters.Rd b/man/ComputePSUSamplingParameters.Rd
index 96f7a26d..5d2f333c 100644
--- a/man/ComputePSUSamplingParameters.Rd
+++ b/man/ComputePSUSamplingParameters.Rd
@@ -6,19 +6,28 @@
 \usage{
 ComputePSUSamplingParameters(
   StoxBioticData,
-  DefinitionMethod = c("AdHocStoxBiotic"),
+  DefinitionMethod = c("AdHocStoxBiotic", "ProportionalPoissonSampling"),
   SamplingUnitId = character(),
-  StratificationColumns = character()
+  StratificationColumns = character(),
+  StratumName = character(),
+  Quota = numeric(),
+  ExpectedSampleSize = numeric()
 )
 }
 \arguments{
 \item{StoxBioticData}{\code{\link[RstoxData]{StoxBioticData}} Sample data to construct design parameters from}
 
-\item{DefinitionMethod}{'AdHocStoxBiotic'}
+\item{DefinitionMethod}{'AdHocStoxBiotic' or 'ProportionalPoissonSampling'}
 
 \item{SamplingUnitId}{name of column in 'StoxBioticData' that identifies the Primary Sampling Unit the design is constructed for.}
 
-\item{StratificationColumns}{name of any column (at the same table as 'SamplingUnitId') that are to be used to define Strata for sampling.}
+\item{StratificationColumns}{name of any column (at the same table as 'SamplingUnitId') that are to be used to define Strata for sampling. (for DefinitionMethod 'AdHocStoxBiotic')}
+
+\item{StratumName}{name of the stratum sampling parameters are calculated for (for DefinitionMethod 'ProportionalPoissonSampling')}
+
+\item{Quota}{expected total catch in sampling frame in kg (for DefinitionMethod 'ProportionalPoissonSampling')}
+
+\item{ExpectedSampleSize}{the expected sample size for Possion sampling (for DefinitionMethod 'ProportionalPoissonSampling')}
 }
 \value{
 \code{\link[RstoxFDA]{PSUSamplingParametersData}}
@@ -34,13 +43,46 @@ selection with replacement and complete response.
 This is a reasonable approximation if within-strata sampling is approximately simple random selections,
 the sample intensitiy is low (only a small fraction of the population is sampled),
 and non-response is believed to be random.
+
+If 'DefinitionMethod' is 'ProportionalPoissonSampling', Unstratified (singe stratum) Poission sampling with selection probabilities
+proportional to catch size is assumed. 'SamplingUnitId' must be a variable on the Haul table of 'StoxBioticData' for this option,
+and the data must contain only one species (SpeciesCategory in 'StoxBioticData'). SelectionProbabilities are assigned
+based on the total catch of the species in each haul. Specifically, for a haul \eqn{i}; selectionprobabilites, \eqn{p_{i}} and inclusionprobabilities \eqn{\pi_{i}}
+are calculated as:
+
+\deqn{p_{i}=\frac{w_{i}}{W}}
+
+\deqn{\pi_{i}=1-(1-p_{i})^{n}}
+
+where:
+\itemize{
+\item \eqn{w_{i}} is the sum of all catch weights in haul \eqn{i} ('CatchFractionWeight' on the 'Sample' table of 'StoxBioticData')
+\item \eqn{W} is the expected total catch in the fishery (argument 'Quota')
+\item \eqn{n} is the expected sample size (argument 'ExpectedSampleSize')
+}
+If proportional poisson sampling was actually used to select the sampled records in 'StoxBioticData',
+sampling parameters would have been obtained prior to sampling, and it is generally preferable to obtain these,
+and import those via \code{\link[RstoxFDA]{ReadPSUSamplingParameters}}. Weight-records are sometimes corrected after
+sampling parameters are calculated, and proper information about non-response can not be recalculated after the fact.
+
+Proportional poisson sampling also allows the sampler to combine rigour and pragmatism, by varying sampling parameters
+in the course of sample selection. For instance 'n' may be changed during the sampling period, if non-response
+turns out to be higher than expected. Such flexibilities are not
+provided by this function, and the approximation may be severely compromised, if such pragmatism is not accounted for.
 }
 \examples{
- # parameters for simpler random haul-selection, stratified by GearGroup
+ # parameters for simple random haul-selection, stratified by GearGroup
  PSUparams <- ComputePSUSamplingParameters(RstoxFDA::StoxBioticDataExample, 
   "AdHocStoxBiotic", 
   "Haul", 
   "GearGroup")
+  
+ # parameters for haul selection proportional to catch size.
+ calculatedPps <- RstoxFDA::ComputePSUSamplingParameters(RstoxFDA::CatchLotteryExample, 
+    "ProportionalPoissonSampling", 
+    "serialnumber", StratumName = 
+    "Nordsjo", Quota = 124*1e6, 
+    ExpectedSampleSize = 110)
 
 }
 \concept{Analytical estimation}
diff --git a/man/processPropertyFormats.Rd b/man/processPropertyFormats.Rd
index 57ccef88..02f64be8 100644
--- a/man/processPropertyFormats.Rd
+++ b/man/processPropertyFormats.Rd
@@ -5,7 +5,7 @@
 \alias{processPropertyFormats}
 \title{Define the process property formats for inclusion in stox UI}
 \format{
-An object of class \code{list} of length 23.
+An object of class \code{list} of length 25.
 }
 \usage{
 processPropertyFormats
diff --git a/man/stoxFunctionAttributes.Rd b/man/stoxFunctionAttributes.Rd
index 60c49506..22f261a6 100644
--- a/man/stoxFunctionAttributes.Rd
+++ b/man/stoxFunctionAttributes.Rd
@@ -5,7 +5,7 @@
 \alias{stoxFunctionAttributes}
 \title{Function specification for inclusion in StoX UI}
 \format{
-An object of class \code{list} of length 59.
+An object of class \code{list} of length 60.
 }
 \usage{
 stoxFunctionAttributes