ReportSuperIndividuals: Report SuperIndividualsData
In StoXProject/RstoxBase: Base StoX Functions

ReportSuperIndividuals

R Documentation

Report SuperIndividualsData

Description

Reports the sum, mean or other functions on a variable of the SuperIndividualsData.

Usage

ReportSuperIndividuals(
  SuperIndividualsData,
  TargetVariable = character(),
  TargetVariableUnit = character(),
  ReportFunction = getReportFunctions(use = "Baseline"),
  GroupingVariables = character(),
  InformationVariables = character(),
  Filter = character(),
  RemoveMissingValues = FALSE,
  WeightingVariable = character(),
  ConditionOperator = character(),
  ConditionValue = character(),
  FractionOverVariable = character()
)

Arguments

`SuperIndividualsData`	The `SuperIndividualsData` data.
`TargetVariable`	The variable to report.
`TargetVariableUnit`	The unit to use for the `TargetVariable`. See RstoxData::StoxUnits for possible units (look for the appropriate quantity, e.g. "length" for IndividualTotalLength, and use the shortname in the `TargetVariableUnit`).
`ReportFunction`	The name of a function to report the Baseline process output by. This must be a function returning a single value. See `ReportFunctions` for implemented funcitons.
`GroupingVariables`	The variables to report by. For most applications `GroupingVariables` should include "Survey" and "SpeciesCategory", unless the user needs to sum over all Survey or SpeciesCategory.
`InformationVariables`	Variables to include as columns to the end of the report table. These cannot have more unique combinations than the `GroupingVariables`.
`Filter`	A string with an R expression to filter out unwanted rows of the report, e.g. "IndividualAge %notin% NA" or "Survey %notin% NA & SpeciesCategory %notin% NA".
`RemoveMissingValues`	Logical: If TRUE, remove missing values (NAs) from the `TargetVariable`. The default (FALSE) implies to report NA if at least one of the values used in the `ReportFunction` is NA. Use `RemoveMissingValues` = TRUE with extreme caution, as it may lead to under-estimation. E.g., if `RemoveMissingValues` = TRUE and a super-individual lacks `IndividualRoundWeight`, `Biomass` will be NA, and the portion of `Abundance` distributed to that super-individual will be excluded when summing `Biomass` (but included when summing `Abundance`). It is advised to always run with `RemoveMissingValues` = FALSE first, and make a thorough investigation to identify the source of any missing values. The function `link{ImputeSuperIndividuals}` can be used to impute the missing information from other super-individuals.
`WeightingVariable`	The variable to weight by. Only relevant for `ReportFunction` "weighted.mean". Note that missing values in the `WeightingVariable` results in missing value from the `weighted.mean` function as per the documentation of this function, regardles of any `RemoveMissingValues`.
`ConditionOperator`, `ConditionValue`	Expressions (strings) giving the condition for the `ReportFunction` `number` and `fractionOfOccurrence`. Supported values for `ConditionOperator` are "%in%", "%notin%", "==", "!=", "%notequal%", "<", "<=", ">=", ">". The `ConditionOperator` and `ConditionValue` are pasted for use in data.table.
`FractionOverVariable`	When `ReportFunction` is a fraction ("fractionOfOccurrence" or "fractionOfSum") `FractionOverVariable` is a string naming the variable (one of the `GroupingVariables`) to sum over in the denominator of the fraction.

Details

This function is useful to, e.g, sum Biomass for each SpeciesCategory and IndividualTotalLength, or average IndividualTotalLength for each IndividualAge and Stratum.