您知道eqdist.etest用于测试执行非参数多样本E统计（能量）检验以确保多元分布是否相等。
我刚刚按照energy文档对我的数据集执行了此测试。
我的数据集由1667个观测值和18个变量组成。
因此，我将代码实现如下：
eqdist.etest(DATABASE, c(555,555,557), R = 199)
但是，它给出了以下错误信息：
Error in eqdist.etest(DATABASE, c(555, 555, 557), R = 199) :
NA/NaN/Inf in foreign function call (arg 1)
In addition: Warning message:
In eqdist.etest(DATABASE, c(555, 555, 557), R = 199) :
NAs introduced by coercion
您可以在我的可复制数据集上对其进行测试
> dput(DATAFINALE[1:20,])
structure(list(AGE_CUSTUMER = c(32L, 37L, 24L, 32L, 44L, 33L,
29L, 30L, 56L, 48L, 44L, 43L, 37L, 43L, 35L, 62L, 60L, 33L, 51L,
32L), MEAN_Sales = c(0, 71.75, 50.71428571, 0, 0.666666667, 83.33333333,
0.333333333, 25.77777778, 23.38461538, 35.52941176, 21.63636364,
46.84615385, 18.4, 15.06666667, 110.25, 8.857142857, 0, 21.5,
18.57142857, 28.125), NBR_GIFTS = c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 4L, 3L, 4L, 2L, 1L, 4L, 1L, 1L, 1L, 1L, 3L, 2L), TYPE_PEAU = c(2L,
3L, 4L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 1L,
4L, 4L, 2L), SENSIBILITE = c(3L, 3L, 3L, 2L, 1L, 3L, 3L, 2L,
2L, 2L, 3L, 1L, 3L, 1L, 2L, 3L, 3L, 2L, 3L, 3L), IMPERFECTIONS = c(2L,
3L, 2L, 1L, 3L, 2L, 2L, 1L, 2L, 1L, 2L, 3L, 2L, 2L, 1L, 3L, 2L,
2L, 2L, 2L), BRILLANCE = c(3L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L), GRAIN_PEAU = c(3L,
3L, 3L, 3L, 1L, 3L, 1L, 1L, 1L, 3L, 3L, 3L, 2L, 1L, 1L, 2L, 1L,
1L, 3L, 3L), RIDES_VISAGE = c(1L, 1L, 1L, 3L, 3L, 3L, 3L, 1L,
3L, 1L, 3L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 3L, 1L), ALLERGIES = c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), MAINS = c(2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 3L, 3L, 2L, 1L, 3L, 3L, 2L, 3L, 3L), PEAU_CORPS = c(1L, 2L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 1L), INTERET_ALIM_NATURELLE = c(1L, 3L, 3L, 1L, 3L, 1L, 1L,
1L, 3L, 1L, 1L, 3L, 1L, 1L, 1L, 2L, 3L, 3L, 1L, 1L), INTERET_ORIGINE_GEO = c(1L,
2L, 1L, 1L, 3L, 1L, 3L, 1L, 1L, 3L, 1L, 1L, 1L, 3L, 1L, 2L, 1L,
1L, 3L, 1L), INTERET_VACANCES = c(2L, 3L, 1L, 2L, 1L, 2L, 1L,
1L, 2L, 3L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 2L, 1L), INTERET_ENVIRONNEMENT = c(1L,
3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L,
1L, 1L, 1L), INTERET_COMPOSITION = c(1L, 1L, 1L, 3L, 3L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 3L, 1L, 1L), OUTCOME = c(3L,
4L, 7L, 3L, 3L, 6L, 3L, 9L, 26L, 17L, 22L, 13L, 10L, 30L, 4L,
7L, 7L, 6L, 14L, 16L)), .Names = c("AGE_CUSTUMER", "MEAN_Sales",
"NBR_GIFTS", "TYPE_PEAU", "SENSIBILITE", "IMPERFECTIONS", "BRILLANCE",
"GRAIN_PEAU", "RIDES_VISAGE", "ALLERGIES", "MAINS", "PEAU_CORPS",
"INTERET_ALIM_NATURELLE", "INTERET_ORIGINE_GEO", "INTERET_VACANCES",
"INTERET_ENVIRONNEMENT", "INTERET_COMPOSITION", "OUTCOME"), row.names = c(1L,
2L, 3L, 5L, 9L, 13L, 14L, 16L, 18L, 19L, 20L, 24L, 27L, 29L,
30L, 32L, 33L, 35L, 36L, 37L), class = "data.frame")