The function prints the vector of entropies for each possible action. Depending on printing options, additional information about the probability calculations can be provided.

print_entropy(entropy, digits = 3, print_all = FALSE)

## Arguments

entropy The entropy measure from calculate_entropy The number of digits to round to. Default 3. If TRUE will print all information on intermediary calculations

## Examples

design <- matrix(c(-1, -1, -1, -1,  1,
-1,  0,  0, -1,  0,
-1,  0, -1,  0,  0,
0,  0, -1,  0, -1), nrow = 4, byrow = TRUE)

entropy <- calculate_entropy(design)

print_entropy(entropy)
#> Shannon's entropy -- Design  1
#>
#>    A1    A2    A3    A4    A5
#> 0.000 0.477 0.000 0.301 0.413
#>
#> print_entropy(entropy, digits = 4)
#> Shannon's entropy -- Design  1
#>
#>     A1     A2     A3     A4     A5
#> 0.0000 0.4771 0.0000 0.3010 0.4127
#>
#> print_entropy(entropy, print_all = TRUE)
#> Shannon's entropy -- Design  1
#>
#>    A1    A2    A3    A4    A5
#> 0.000 0.477 0.000 0.301 0.413
#>
#>
#> The rules-action matrix
#>
#> Rows: Rules
#> Columns: Actions
#>
#>    A1 A2 A3 A4 A5
#> R1 -1 -1 -1 -1  1
#> R2 -1  0  0 -1  0
#> R3 -1  0 -1  0  0
#> R4  0  0 -1  0 -1
#>
#> The considered rule is N/A.
#>
#> The vector of prior probabilities
#>
#>   R1   R2   R3   R4
#> 0.25 0.25 0.25 0.25
#>
#> The probability of an action conditional on a rule
#>
#>       A1    A2    A3    A4    A5
#> R1 0.000 0.000 0.000 0.000 1.000
#> R2 0.000 0.333 0.333 0.000 0.333
#> R3 0.000 0.333 0.000 0.333 0.333
#> R4 0.333 0.333 0.000 0.333 0.000
#>
#> The probability of a rule conditional on observing an action, i.e. the posterior
#>
#>    A1    A2 A3  A4  A5
#> R1  0 0.000  0 0.0 0.6
#> R2  0 0.333  1 0.0 0.2
#> R3  0 0.333  0 0.5 0.2
#> R4  1 0.333  0 0.5 0.0
#>
#>