How to calculate the weighted percentile?

[hsluoyz]

See: https://en.wikipedia.org/wiki/Percentile#The_weighted_percentile_method

My current code is as follows. But I don't know how to support weighted percentile?

func TestPercentile(t *testing.T) {
	values := []float64{4, 5, 3, 1, 2}
	percentiles := []float64{}
	for i := 1; i <= 100; i++ {
		percentile, err := stats.PercentileNearestRank(values, float64(i))
		if err != nil {
			panic(err)
		}
		percentiles = append(percentiles, percentile)
		fmt.Printf("%d%%: %f, ", i, percentile)
	}
	println()
	println()

	for f := 0.0; f <= 5; f += 0.1 {
		index := sort.SearchFloat64s(percentiles, f + 0.00000001)
		fmt.Printf("%f: %d%%, ", f, index)
	}
	println()
	println()
}

[montanaflynn]

There is no built in weighted percentile function in this library. The actual algorithm to use depends on what you're looking for or why you need it.

Do you have an example array and associated weights or can you describe the problem you're trying to solve?

[hsluoyz]

@montanaflynn thanks for answering. See something similar in Python: https://stackoverflow.com/questions/21844024/weighted-percentile-using-numpy

from statsmodels.stats.weightstats import DescrStatsW
wq = DescrStatsW(data=np.array([1, 2, 9, 3.2, 4]), weights=np.array([0.0, 0.5, 1.0, 0.3, 0.5]))
wq.quantile(probs=np.array([0.1, 0.9]), return_pandas=False)
# array([2., 9.])

So I want something like:

percentile, err := stats.PercentileNearestRankWithWeight(values, valueWeights, float64(i))

valueWeights is the weight slice for values. For the original PercentileNearestRank() function, we can view its valueWeights is an all-one slice.