Default scenario parameters.

Returns default parameters for scenarios. Use this function to get a combination of disturbanceDefaults(), timeDefaults(), demographyDefaults(), nationalTrajectoryDefaults(), and monitoringDefaults(). If only one of these sets of parameters is needed consider using the relevant component function instead.

Usage

getScenarioDefaults(
  paramTable = NULL,
  includeDist = T,
  includeTime = T,
  includeDemography = T,
  includeNational = T,
  includeMonitoring = T,
  ...
)

Arguments

paramTable

a data.frame with column names matching the arguments below. Any columns that are missing will be filled with the default values.

includeDist

logical. Include disturbanceDefaults()?

includeTime

logical. Include timeDefaults()?

includeDemography

logical. Include demographyDefaults()?

includeNational

logical. Include nationalTrajectoryDefaults()?

includeMonitoring

logical. Include monitoringDefaults()?

Value

a data.frame of parameter values including a label that combines all the parameter names and values into a string

See also

Caribou demography functions: bayesianScenariosWorkflow(), bayesianTrajectoryWorkflow(), betaNationalPriors(), caribouPopGrowth(), compareTrajectories(), compositionBiasCorrection(), convertTrajectories(), dataFromSheets(), demographicProjectionApp(), demographyDefaults(), disturbanceDefaults(), estimateBayesianRates(), estimateNationalRate(), getNationalCoefficients(), monitoringDefaults(), nationalTrajectoryDefaults(), plotCompareTrajectories(), plotSurvivalSeries(), plotTrajectories(), popGrowthTableJohnsonECCC, simulateObservations(), timeDefaults(), trajectoriesFromBayesian(), trajectoriesFromNational(), trajectoriesFromSummary(), trajectoriesFromSummaryForApp()

Examples

getScenarioDefaults()
#> # A tibble: 1 × 24
#>      N0  qMin  qMax  uMin  uMax  zMin  zMax cowMult correlateRates rSlopeMod
#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>   <dbl> <lgl>              <dbl>
#> 1  1000     0     0     0     0     0     0       6 FALSE                  1
#> # ℹ 14 more variables: sSlopeMod <dbl>, interannualVar <list>, iFire <dbl>,
#> #   iAnthro <dbl>, obsAnthroSlope <dbl>, projAnthroSlope <dbl>, hasYear <lgl>,
#> #   projYears <dbl>, obsYears <dbl>, preYears <dbl>, curYear <dbl>,
#> #   startYear <dbl>, ID <int>, label <chr>

# paramTable list takes precedence over argument values
getScenarioDefaults(paramTable = data.frame(iFire = 10, iAnthro = 20, obsYears = 1), obsYears = 5)
#>     N0 qMin qMax uMin uMax zMin zMax cowMult correlateRates rSlopeMod sSlopeMod
#> 1 1000    0    0    0    0    0    0       6          FALSE         1         1
#>     interannualVar iFire iAnthro obsAnthroSlope projAnthroSlope hasYear
#> 1 0.46000, 0.08696    10      20              2               2   FALSE
#>   projYears obsYears preYears curYear startYear ID
#> 1        35        1        0    2023      2023  1
#>                                                                                                                                                                                                                                                                          label
#> 1 ID1_startYear2023_curYear2023_preYears0_obsYears1_projYears35_hasYearFALSE_projAnthroSlope2_obsAnthroSlope2_iAnthro20_iFire10_interannualVarlist(R_CV = 0.46, S_CV = 0.08696)_sSlopeMod1_rSlopeMod1_correlateRatesFALSE_cowMult6_zMax0_zMin0_uMax0_uMin0_qMax0_qMin0_N01000_