mkurtosisTopN

语法

mkurtosisTopN(X, S, window, top, [biased=true], [ascending=true], [tiesMethod='latest'])

参数说明和窗口计算规则请参考:mTopN

参数

biased 是一个布尔值,表示是否是有偏估计。默认值为 true,表示有偏估计。

详情

在给定长度(以元素个数衡量)的滑动窗口内,根据 ascending 指定的排序方式将 X 按照 S 进行稳定排序后,取前 top 个元素计算峰度。

返回值:DOUBLE 类型。

例子

X=1 2 3 10 100 4 3
S = 0.3 0.5 0.1 0.1 0.5 0.2 0.4
mkurtosisTopN(X, S, 6, 4)
# output
[,,1.49,2.23,2.31,2.11,2.27]

X = matrix(1..10, 11..20)
S = matrix(2022.01.01 2022.02.03 2022.01.23 NULL 2021.12.29 2022.01.20 2022.01.23 2022.01.22 2022.01.24 2022.01.24, NULL 2022.02.03 2022.01.23 2022.04.06 NULL 2022.02.03 2022.02.03 2022.02.05 2022.02.08 2022.02.03)
mkurtosisTopN(X, S, 6, 4)
col1 col2
1.5
1.5 1.5
1.8457 1.5
1.5734 1.8457
1.8457 1.2215
1.64 2
1.64 1.64
1.64 1.8457
symbol = ["A","A","A","B","A","A","B","A","A","B","B","B","A","B","A","B","B","A","B","A"]
time = temporalAdd(2023.07.05T09:30:00.000,[10,20,40,60,70,80,90,140,160,170,180,190,200,210,220,230,250,360,390,400],"ms")
price = [28.11,28.25,28.44,52.31,28.98,28.89,52.22,28.16,28.52,52.62,52.56,52.2,28.01,52.43,28.57,52.42,52.19,28.16,52.84,28.18]
qty = [5000,400,3100,100,2400,3700,700,3700,4600,4700,3100,3300,3900,3500,3000,3000,4000,4700,2000,4400]
BSFlag = [1,0,0,0,1,1,0,1,0,0,0,1,0,0,1,1,1,0,1,0]
t = table(time, symbol, price, qty, BSFlag)
select time,symbol,mkurtosisTopN(price, qty, 8, 5) as mskewTop5price from t context by symbol
time symbol mskewTop5price
2023.07.05T09:30:00.010 A
2023.07.05T09:30:00.020 A
2023.07.05T09:30:00.040 A 1.5
2023.07.05T09:30:00.070 A 2.0147
2023.07.05T09:30:00.080 A 1.3355
2023.07.05T09:30:00.140 A 1.2976
2023.07.05T09:30:00.160 A 1.2976
2023.07.05T09:30:00.200 A 1.2976
2023.07.05T09:30:00.220 A 2.2021
2023.07.05T09:30:00.360 A 1.656
2023.07.05T09:30:00.400 A 1.351
2023.07.05T09:30:00.060 B
2023.07.05T09:30:00.090 B
2023.07.05T09:30:00.170 B 1.5
2023.07.05T09:30:00.180 B 1.1993
2023.07.05T09:30:00.190 B 1.289
2023.07.05T09:30:00.210 B 1.7383
2023.07.05T09:30:00.230 B 1.8183
2023.07.05T09:30:00.250 B 1.8183
2023.07.05T09:30:00.390 B 1.923

相关函数:mkurtosis