Finds the number of bins in x and y direction which gives the maximum binned distance.

Source: R/opt_diff.r

This function finds the optimal number of bins in both x and y direction which should be used to calculate the binned distance. The binned distance is calculated for each combination of provided choices of number of bins in x and y direction and finds the difference using calc_diff for each combination. The combination for which the difference is maximum should be used.

opt_bin_diff(
  lineup.dat,
  var,
  xlow,
  xhigh,
  ylow,
  yhigh,
  pos,
  plot = FALSE,
  m = 20
)

Arguments

lineup.dat

lineup data to get the lineup

var

a list of names of the variables to be used to calculate the difference

xlow

the lowest value of number of bins on the x-direction

xhigh

the highest value of number of bins on the x-direction

ylow

the lowest value of number of bins on the y-direction

yhigh

the highest value of number of bins on the y-direction

pos

position of the true plot in the lineup

plot

LOGICAL; if true, returns a tile plot for the combinations of number of bins with the differences as weights

m

number of plots in the lineup, by default m = 20

Value

a dataframe with the number of bins and differences the maximum mean distance of the null plots

Examples

if(require('dplyr')){
opt_bin_diff(lineup(null_permute('mpg'), mtcars, pos = 1), var = c('mpg', 'wt'),
2, 5, 4, 8, pos = 1, plot = TRUE, m = 8)
}
#> $dat
#> # A tibble: 20 × 3
#> # Groups:   xbins [4]
#>    xbins ybins    Diff
#>    <int> <int>   <dbl>
#>  1     2     4 -0.409 
#>  2     2     5 -0.409 
#>  3     2     6 -0.387 
#>  4     2     7 -0.409 
#>  5     2     8 -0.409 
#>  6     3     4  0.449 
#>  7     3     5  0.449 
#>  8     3     6  0.0697
#>  9     3     7  0.449 
#> 10     3     8  0.449 
#> 11     4     4  0.151 
#> 12     4     5  0.151 
#> 13     4     6  0.238 
#> 14     4     7  0.151 
#> 15     4     8  0.151 
#> 16     5     4  0.759 
#> 17     5     5  0.759 
#> 18     5     6  0.207 
#> 19     5     7  0.759 
#> 20     5     8  0.759 
#> 
#> $p

#>