Description Usage Arguments Details Value Examples
runBootstrap
is a wrapper function for the bootstrap functions below.
runBootstrap_1.6
runs the bootstrap of Rstox 1.6. The bootstrap changed from Rstox 1.6 to 1.7, by applying sorting prior to sampling, and different results (but with the same expected value) should be expected. Using runBootstrap_1.6
identical results from previous runs should be expected.
runBootstrap_AcousticTrawl
runs a simple bootstrap of biotic PSUs within strata.
runBootstrap_SweptAreaLength
runs a simple bootstrap of biotic PSUs within strata.
runBootstrap_SweptAreaTotal
runs a simple bootstrap of biotic PSUs within strata.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | runBootstrap(projectName, bootstrapMethod = "AcousticTrawl",
acousticMethod = PSU ~ Stratum, bioticMethod = PSU ~ Stratum,
nboot = 5, startProcess = "TotalLengthDist",
endProcess = "SuperIndAbundance", seed = 1, cores = 1,
msg = TRUE, sorted = TRUE, JavaMem = getRstoxDef("JavaMem"), ...)
runBootstrap_1.6(projectName, bootstrapMethod = "AcousticTrawl",
acousticMethod = PSU ~ Stratum, bioticMethod = PSU ~ Stratum,
nboot = 5, startProcess = "TotalLengthDist",
endProcess = "SuperIndAbundance", seed = 1, cores = 1,
msg = TRUE, ...)
runBootstrap_AcousticTrawl(projectName, acousticMethod = PSU ~ Stratum,
bioticMethod = PSU ~ Stratum, nboot = 5,
startProcess = "TotalLengthDist", endProcess = "SuperIndAbundance",
seed = 1, cores = 1, msg = TRUE, sorted = TRUE,
JavaMem = getRstoxDef("JavaMem"), ...)
runBootstrap_SweptAreaLength(projectName, acousticMethod = NULL,
bioticMethod = PSU ~ Stratum, nboot = 5,
startProcess = "TotalLengthDist", endProcess = "SuperIndAbundance",
seed = 1, cores = 1, msg = TRUE, sorted = TRUE,
JavaMem = getRstoxDef("JavaMem"), ...)
runBootstrap_SweptAreaTotal(projectName, acousticMethod = NULL,
bioticMethod = PSU ~ Stratum, startProcess = "SweptAreaDensity",
endProcess = NULL, nboot = 5, seed = 1, cores = 1,
ignore.case = TRUE, sorted = TRUE, ...)
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projectName |
The name or full path of the project, a baseline object (as returned from | |||||||||||||||||||||
bootstrapMethod |
The method to use for the bootstrap. Currently implemented are given in the following table:
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acousticMethod, bioticMethod |
Specification of the method to use for bootstrapping the acoustic and biotic data. Currently only one method is available for acoustic and one for biotic data: acousticMethod = PSU~Stratum, bioticMethod = PSU~Stratum. Other methods are planned in later versions, involving the levels of the data given in the below table.
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nboot |
Number of bootstrap replicates. | |||||||||||||||||||||
startProcess |
The start process of the bootstrapping, e.g., the last process before bio-stations have been assigned and NASC values have been calculated. | |||||||||||||||||||||
endProcess |
The end process of the bootstrapping, e.g., the process returning a matrix containing the following columns: "Stratum", "Abundance", "weight", and grouping variables such as "age", "SpecCat", "sex" (typically "SuperIndAbundance"). | |||||||||||||||||||||
seed |
The seed for the random number generator (used for reproducibility). | |||||||||||||||||||||
cores |
An integer giving the number of cores to run the bootstrapping over. | |||||||||||||||||||||
msg |
Logical: if TRUE print messages from runBaseline(). | |||||||||||||||||||||
sorted |
Should the data be sorted prior to sampling? | |||||||||||||||||||||
JavaMem |
The memory occupied by the Java virtual machine. Default is returned by getRstoxDef("JavaMem"). Reducing this may be usefull when using mutiple cores. | |||||||||||||||||||||
... |
Used for backwards compatibility. | |||||||||||||||||||||
ignore.case |
Logical: If TRUE ignore case in species category SpecCat. |
Resample (bootstrap) trawl stations based on swept area data and possibly also acoustic data to estimate uncertainty in estimates. By the default method (bootstrapMethod="AcousticTrawl"), the acoustic transect values (mean NASC along transects) and biotic stations (trawls) are resampled with replacement within each stratum for each bootstrap replicate, and the StoX project rerun and super individual abundance recalculated (or the output from a different process given by endProcess
).
list with (1) the abundance by length in the orginal model, (2) the abundance by length in the bootstrap run, (3) the abundance by super individuals in the orginal model, (4) the abundance by super individuals in the bootstrap run
1 2 3 4 5 | ## Not run:
projectName <- "Test_Rstox"
boot <- runBootstrap(projectName, nboot=10, seed=1, bootstrapMethod="AcousticTrawl")
## End(Not run)
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