我有一个66个数字的矢量，称为a，每个都有一个名字：
Age0_i0 Age1_i0 Age1_i1 Age2_i0 Age2_i1 Age2_i2 Age3_i0 Age3_i1 Age3_i2
1000000.000 680000.000 170000.000 462400.000 115600.000 144500.000 314432.000 78608.000 98260.000
Age3_i3 Age4_i0 Age4_i1 Age4_i2 Age4_i3 Age4_i4 Age5_i0 Age5_i1 Age5_i2
122825.000 213813.760 53453.440 66816.800 83521.000 104401.250 145393.357 36348.339 45435.424
Age5_i3 Age5_i4 Age5_i5 Age6_i0 Age6_i1 Age6_i2 Age6_i3 Age6_i4 Age6_i5
56794.280 70992.850 88741.062 98867.483 24716.871 30896.088 38620.110 48275.138 60343.922
Age6_i6 Age7_i0 Age7_i1 Age7_i2 Age7_i3 Age7_i4 Age7_i5 Age7_i6 Age7_i7
75429.903 67229.888 16807.472 21009.340 26261.675 32827.094 41033.867 51292.334 64115.418
Age8_i0 Age8_i1 Age8_i2 Age8_i3 Age8_i4 Age8_i5 Age8_i6 Age8_i7 Age8_i8
45716.324 11429.081 14286.351 17857.939 22322.424 27903.030 34878.787 43598.484 54498.105
Age9_i0 Age9_i1 Age9_i2 Age9_i3 Age9_i4 Age9_i5 Age9_i6 Age9_i7 Age9_i8
31087.100 7771.775 9714.719 12143.399 15179.248 18974.060 23717.575 29646.969 37058.711
Age9_i9 Age10_i0 Age10_i1 Age10_i2 Age10_i3 Age10_i4 Age10_i5 Age10_i6 Age10_i7
46323.389 21139.228 5284.807 6606.009 8257.511 10321.889 12902.361 16127.951 20159.939
Age10_i8 Age10_i9 Age10_i10
25199.924 31499.905 39374.881
我想生成一些这些向量的总和列表。具体来说，我想将Age3_i3，Age3_i4 ......到Age3_i10的所有Age3s相加。然后所有Age4s从_i3到_i10和Age5s _i3到_i10一直到Age10 _i3到_i10。我想在这样的循环中做到这一点：
x <- 10
for (i in 3:x){
for (j in 3:i){
s <- sum(a[paste0("Age",i,"_i",j)])
}}
取值
但它只给了我一个[66]，a的最后一个值。理想情况下，它会给我一个8个总计的列表。
任何帮助表示赞赏！
添加dput数据：
structure(c(1e+06, 680000, 170000, 462400, 115600, 144500, 314432,
78608, 98260, 122825, 213813.76, 53453.44, 66816.8, 83521, 104401.25,
145393.357, 36348.339, 45435.424, 56794.28, 70992.85, 88741.062,
98867.483, 24716.871, 30896.088, 38620.11, 48275.138, 60343.922,
75429.903, 67229.888, 16807.472, 21009.34, 26261.675, 32827.094,
41033.867, 51292.334, 64115.418, 45716.324, 11429.081, 14286.351,
17857.939, 22322.424, 27903.03, 34878.787, 43598.484, 54498.105,
31087.1, 7771.775, 9714.719, 12143.399, 15179.248, 18974.06,
23717.575, 29646.969, 37058.711, 46323.389, 21139.228, 5284.807,
6606.009, 8257.511, 10321.889, 12902.361, 16127.951, 20159.939,
25199.924, 31499.905, 39374.881), .Names = c("Age0_i0", "Age1_i0",
"Age1_i1", "Age2_i0", "Age2_i1", "Age2_i2", "Age3_i0", "Age3_i1",
"Age3_i2", "Age3_i3", "Age4_i0", "Age4_i1", "Age4_i2", "Age4_i3",
"Age4_i4", "Age5_i0", "Age5_i1", "Age5_i2", "Age5_i3", "Age5_i4",
"Age5_i5", "Age6_i0", "Age6_i1", "Age6_i2", "Age6_i3", "Age6_i4",
"Age6_i5", "Age6_i6", "Age7_i0", "Age7_i1", "Age7_i2", "Age7_i3",
"Age7_i4", "Age7_i5", "Age7_i6", "Age7_i7", "Age8_i0", "Age8_i1",
"Age8_i2", "Age8_i3", "Age8_i4", "Age8_i5", "Age8_i6", "Age8_i7",
"Age8_i8", "Age9_i0", "Age9_i1", "Age9_i2", "Age9_i3", "Age9_i4",
"Age9_i5", "Age9_i6", "Age9_i7", "Age9_i8", "Age9_i9", "Age10_i0",
"Age10_i1", "Age10_i2", "Age10_i3", "Age10_i4", "Age10_i5", "Age10_i6",
"Age10_i7", "Age10_i8", "Age10_i9", "Age10_i10"))
答案 0 :(得分：1)
我认为你可以使用聪明的grep：
nn <- names(y)
sapply (c(3,4,5) ,function(i)
sum(y[grep(paste0('Age',i,'_i10|Age',i,'_i','[3-9]'),nn)]))
[1] 122825.0 187922.2 216528.2
此解决方案适用于任何范围（最小值，最大值）。它生成一个序列并使用na.rm参数来删除缺失值。效率较低（产生的数量超过需要），但总是有效并且不使用正则表达式。
sum_filter <-
function(min=3,max=10)
sapply (c(3,4,5) ,function(i)
sum(y[paste0('Age',i,'_i',seq(min,max))],na.rm=T))
答案 1 :(得分：1)
构造您想要的名称，然后按它们进行子集化：
nm = expand.grid(age = 3:5, id = 3:10)
sum(y[paste0('Age', nm$age, '_i', nm$id)], na.rm = T)
#[1] 527275.4
如果你想要为每个年龄组想要这些总和，我会改为
library(data.table)
nm = CJ(age = 3:5, id = 3:10)
nm[, sum(y[paste0('Age', age, '_i', id)], na.rm = T), by = age]
# age V1
#1: 3 122825.0
#2: 4 187922.2
#3: 5 216528.2