使用Boost计算百分位（P50、P95）

Question

我正在尝试计算 P50 和 P95 以用于整数流列表。这是示例代码：Live On Compiler Explorer

#include <boost/accumulators/accumulators.hpp>
#include <boost/accumulators/statistics.hpp>
#include <boost/accumulators/statistics/extended_p_square_quantile.hpp>
namespace ba = boost::accumulators;
int main() {
    std::vector<int>    values = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
    std::vector<double> probs  = {0.5, 0.95};

    ba::accumulator_set<int, ba::stats<ba::tag::extended_p_square_quantile>> //
        acc(ba::extended_p_square_probabilities = probs);

    for (auto val : values) {
        acc(val);
    }

    std::cout << "P: " << ba::quantile(acc, ba::quantile_probability = 0.5) << " "
              << ba::quantile(acc, ba::quantile_probability = 0.95) << std::endl;
}

但这返回了意想不到的值：

P: 3 7

我预计答案是

5 9

。我怎样才能得到我想要的东西？

Answer 1

统计数据为估计值。您不仅应该期望不同的值。也许 95% 的百分位数估计应该更接近 10。

您可以通过测试程序的扩展来看到它的工作原理：

住在Coliru

#include <boost/accumulators/accumulators.hpp>
#include <boost/accumulators/statistics.hpp>
#include <boost/accumulators/statistics/extended_p_square_quantile.hpp>
namespace ba  = boost::accumulators;
namespace tag = ba::tag;

template <typename... T> using Accum = ba::accumulator_set<int, ba::stats<T...>>;

template <typename... T> Accum<T...> make() {
    std::vector<double> probs = {0.5, 0.95};
    // unused arguments are ignored
    return Accum<T...>(ba::extended_p_square_probabilities              = probs,
                       tag::p_square_cumulative_distribution::num_cells = 11);
}

int main() {
    std::vector<int> values = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};

    auto simple   = make<tag::median>();
    auto p_sq_est = make<tag::with_p_square_cumulative_distribution_median>();
    auto acc      = make<tag::extended_p_square_quantile_quadratic>();

    for (int i = 0; i < 100; ++i) {
        for (auto val : values) {
            simple(val);
            p_sq_est(val);
            acc(val);
        }

        printf("P: %6.3f %6.3f  simple: %6.3f p_sq_est: %6.3f\n", //
               ba::quantile(acc, ba::quantile_probability = 0.50),              //
               ba::quantile(acc, ba::quantile_probability = 0.95),              //
               ba::median(simple), ba::median(p_sq_est));
    }
}

印刷：

P:  3.000  7.000  simple:  5.000 p_sq_est:  6.000
P:  5.500  9.000  simple:  5.231 p_sq_est:  6.281
P:  5.286  9.433  simple:  5.448 p_sq_est:  6.004
P:  5.460  9.688  simple:  5.346 p_sq_est:  6.136
P:  5.396  9.835  simple:  5.285 p_sq_est:  6.184
P:  5.353  9.835  simple:  5.240 p_sq_est:  6.201
P:  5.321  9.910  simple:  5.204 p_sq_est:  6.166
P:  5.297  9.951  simple:  5.175 p_sq_est:  6.263
// ...
P:  5.130 10.000  simple:  5.011 p_sq_est:  6.523
P:  5.129 10.000  simple:  5.011 p_sq_est:  6.511
P:  5.129 10.000  simple:  5.011 p_sq_est:  6.511
P:  5.129 10.000  simple:  5.011 p_sq_est:  6.517
P:  5.129 10.000  simple:  5.011 p_sq_est:  6.511