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stats::a_quantil -- alpha-quantile of discrete data

Introduction

stats::a_quantil(a, ..) returns the alpha-quantile of discrete data.

Call(s)

stats::a_quantil(a, x1, x2, ..)
stats::a_quantil(a, [x1, x2, ..])
stats::a_quantil(a, s <, c>)

Parameters

a - the alpha value: a rational number or a real float from the interval (0,1).
x1, x2, .. - the statistical data: real numerical values.
s - a sample of domain type stats::sample.
c - an integer representing a column index of the sample s. This column provides the data x1, x2 etc.

Returns

an arithmetical expression. FAIL is returned, if the data are empty.

Related Functions

stats::geometric, stats::harmonic, stats::mean, stats::median, stats::modal, stats::quadratic, stats::stdev, stats::variance

Details

Example 1

We calculate the 1/4-quantile of a sequence of five values:

>> stats::a_quantil(1/4, 3, 8, 5, 9/2, 11)
   
                                    9/2
      

Alternatively, the data may be passed as a list:

>> stats::a_quantil(1/4, [3, 8, 5, 9/2, 11])
   
                                    9/2
      

Example 2

We create a sample:

>> stats::sample([[4, 7, 5], [3, 6, 17], [8, 2, 2]])
   
                                4  7   5
                                3  6  17
                                8  2   2
      

The 1/2-quantile (the median) of the second column is calculated:

>> stats::a_quantil(1/2, %, 2)
   
                                     6
      

Example 3

We create a sample consisting of one string column and one non-string column:

>> stats::sample([["1996", 1242], ["1997", 1353], ["1998", 1142]])
   
                              "1996"  1242
                              "1997"  1353
                              "1998"  1142
      

The 0.3-quantile of the second column is calculated. In this case this column does not have to be specified, since it is the only non-string column in the sample:

>> stats::a_quantil(0.3, %)
   
                                   1142
      

Changes




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