boot_simulated_cat_bin: Confidence-interval bootstraps on simulated independent...
In foodingraph: Food Network Inference and Visualization

Description Usage Arguments Value References Examples

View source: R/boot_simulated_cat_bin.R

Create a defined number of simulated independent random variables of a given size according to type : 2 ordinal variables, 2 binary variables, 1 binary and 1 ordinal variable. A number of bootstraps are then performed on the sample to calculate a confidence interval of the bootstrap distribution of the chosen method: mutual information or the maximal information coefficient. The percentile method is used to calculate this interval.

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boot_simulated_cat_bin(type = c("cat", "bin", "bincat"),
  method = c("mic", "mi"), simu = 10, boots = 5000, size = 500,
  percentile = 0.99)

`type`	: the type of the simulated variables: `cat` is for 2 ordinal variables, `bin` is for 2 binary variables, `bincat` is for 1 binary and 1 ordinal variable.
`method`	: the method used to calculate the association : mutual information (`mi`), or the maximal information coefficient (`mic`).
`simu`	: the number of simulated pairs of variables. For each pair, the confidence-interval bootstrap is calculated from the bootstrap distribution of the MI/MIC of between the two pairs. At the end of the program, the mean of the chosen percentile is given. Default is 10.
`boots`	: the number of bootstraps per simulation. Default is 5000.
`size`	: the size of the sample. Default is 500.
`percentile`	: the percentile kept. Default is 0.99 (the 99th percentile).