This is a wrapper around shakers that allows to run it k times
and adds and index to the resulting tibble. As the typical entry point in permutationnal
analysis it also checks your data to avoid further problems.
Arguments
- x
tibble()- k
number of new datasets to create
- shaker
one of the shaker functions (
shake_uniform()by default)- ...
arguments expected by the selected shaker function. They must be provided and named. See examples
Examples
set.seed(2329) # replicability
# shaking uniform
df_u
#> # A tibble: 8 × 5
#> tpq taq species site mes
#> <dbl> <dbl> <chr> <chr> <dbl>
#> 1 34 43 fox a 1.22
#> 2 -90 -46 fox a 1.90
#> 3 87 98 fox b 2.94
#> 4 5 32 fox b 4.38
#> 5 -95 -85 hound a 4.35
#> 6 42 69 hound a 2.91
#> 7 10 50 hound b 1.58
#> 8 27 46 hound b 1.45
df_u %>% quake(k=5, shake_uniform, min=tpq, max=taq)
#> * quake . using shake_uniform
#> * launching 5 permutations
#> # A tibble: 40 × 7
#> k tpq taq species site mes x_new
#> <int> <dbl> <dbl> <chr> <chr> <dbl> <dbl>
#> 1 1 34 43 fox a 1.22 40.0
#> 2 1 -90 -46 fox a 1.90 -87.8
#> 3 1 87 98 fox b 2.94 97.3
#> 4 1 5 32 fox b 4.38 19.2
#> 5 1 -95 -85 hound a 4.35 -94.8
#> 6 1 42 69 hound a 2.91 61.2
#> 7 1 10 50 hound b 1.58 32.0
#> 8 1 27 46 hound b 1.45 39.1
#> 9 2 34 43 fox a 1.22 34.7
#> 10 2 -90 -46 fox a 1.90 -52.2
#> # … with 30 more rows
# not that you can omit shakers' argument names, providing they come in the right order
# eg: df_u %>% quake(k=5, shake_uniform, tpq, taq)
# shaking gaussian
df_g
#> # A tibble: 8 × 5
#> c14 sd1 species site mes
#> <dbl> <dbl> <chr> <chr> <dbl>
#> 1 34 6 fox a 1.22
#> 2 -90 18 fox a 1.90
#> 3 87 7 fox b 2.94
#> 4 5 12 fox b 4.38
#> 5 -95 7 hound a 4.35
#> 6 42 12 hound a 2.91
#> 7 10 17 hound b 1.58
#> 8 27 10 hound b 1.45
df_g %>% quake(k=5, shake_gaussian, mean=c14, sd=sd1)
#> * quake . using shake_gaussian
#> * launching 5 permutations
#> # A tibble: 40 × 7
#> k c14 sd1 species site mes x_new
#> <int> <dbl> <dbl> <chr> <chr> <dbl> <dbl>
#> 1 1 34 6 fox a 1.22 36.2
#> 2 1 -90 18 fox a 1.90 -96.4
#> 3 1 87 7 fox b 2.94 88.3
#> 4 1 5 12 fox b 4.38 14.2
#> 5 1 -95 7 hound a 4.35 -96.7
#> 6 1 42 12 hound a 2.91 41.2
#> 7 1 10 17 hound b 1.58 7.63
#> 8 1 27 10 hound b 1.45 38.5
#> 9 2 34 6 fox a 1.22 41.8
#> 10 2 -90 18 fox a 1.90 -84.5
#> # … with 30 more rows
# on a more realistic dataset bigger baby:
# animals %>% quake(k=2, shake_uniform, tpq, taq)