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Calculate quantile f-values

Source: R/eda_fval.R
eda_fval.Rd

Calculates Fractional Values (f-Values).

Usage

eda_fval(x, q.type = 5)

Arguments

x

Vector whose f-values are to be computed.

q.type

An integer specifying the algorithm to use for computing F-values.

Value

A numeric vector of the same length as x, containing the f-values for each input value. The order of the returned f-values matches the input vector.

Details

This function computes the fractional value (f-value) for each element in a numeric vector x. The f-value provides a measure of the position of a data point relative to the rest of the data, scaled to the range [0,1]. This fraction is sometimes reported as the probability or cumulative frequency.

Different algorithms are used to compute the f-value. eda_fval offers as optional algorithm type 4 through 9 documented in stats::quantile. The algorithms used are:

  • 4: f = i / n,

  • 5: f = (i - 0.5) / n,

  • 6: f = i / (n + 1),

  • 7: f = (i - 1) / (n - 1),

  • 8: f = (i - 1/3) / (n + 1/3),

  • 9: f = (i - 3/8) / (n + 1/4).

Where f is the fraction of values that lies below index i, and n is the total number values.

References

  • John M. Chambers, William S. Cleveland, Beat Kleiner, Paul A. Tukey. Graphical Methods for Data Analysis (1983)

See also

Examples


 set.seed(321)
 z <- round(runif(10, 1, 20))
 z
#>  [1] 19 19  6  6  8  7 10  7 10 16

 # William Cleveland's f-values algorithm
 eda_fval(z)
#>  [1] 0.85 0.95 0.05 0.15 0.45 0.25 0.55 0.35 0.65 0.75

 # Algorithm used by the stats::quantile() function
 eda_fval(z, q.type = 7)
#>  [1] 0.8888889 1.0000000 0.0000000 0.1111111 0.4444444 0.2222222 0.5555556
#>  [8] 0.3333333 0.6666667 0.7777778