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Method jackknife

Source: R/jackknife.R
jackknife.Rd

Jackknife resampling

Usage

# S4 method for class 'FLQuant'
jackknife(object, dim = "year", na.rm = TRUE)

# S4 method for class 'FLQuants'
jackknife(object, ...)

# S4 method for class 'FLModel'
jackknife(object, slot)

Details

The jackknife method sets up objects ready for jackknifing, i.e. to systematically recompute a given statistic leaving out one observation at a time. From this new set of "observations" for the statistic, estimates for the bias and variance of the statstic can be calculated.

Input objects cannot have length > 1 along the iter dimension, and the main slot in the resulting object will have as many iters as the number of elements in the original object that are not NA.

Generic function

jackknife(object, ...)

See also

FLQuantJK FLParJK

Author

The FLR Team

Examples


flq <- FLQuant(1:8)
flj <- jackknife(flq)
iters(flj)
#> -- iter:  1 
#>  1  2  3  4  5  6  7  8 
#> NA  2  3  4  5  6  7  8 
#> -- iter:  2 
#>  1  2  3  4  5  6  7  8 
#>  1 NA  3  4  5  6  7  8 
#> -- iter:  3 
#>  1  2  3  4  5  6  7  8 
#>  1  2 NA  4  5  6  7  8 
#> -- iter:  4 
#>  1  2  3  4  5  6  7  8 
#>  1  2  3 NA  5  6  7  8 
#> -- iter:  5 
#>  1  2  3  4  5  6  7  8 
#>  1  2  3  4 NA  6  7  8 
#> -- iter:  6 
#>  1  2  3  4  5  6  7  8 
#>  1  2  3  4  5 NA  7  8 
#> -- iter:  7 
#>  1  2  3  4  5  6  7  8 
#>  1  2  3  4  5  6 NA  8 
#> -- iter:  8 
#>  1  2  3  4  5  6  7  8 
#>  1  2  3  4  5  6  7 NA 
#> 
#> units:  NA 
#> NULL