您好，
我正在尝试对每个组进行线性回归。你可以在图片上看到每个小组都有一个索引。第1-3列是度量，我的分组列是4,5,6,7,8（存储在名称中）。
我的代码：
grup=setDT(data)[,.("1" = coef(lm(data$`3`~data$id))[1] ) ,by=name]
第4,5,6,7,8列的分组效果很好，第3列的回归没有。 我希望每个组都有回归，如果只有一个值，则应该是1 =没有增加或减少。相反，我为每一行获得相同的值，似乎回归遍历所有行，它只能针对特定组的行。
我用Google搜索了我的**但似乎太傻了，因为我的眼睛开始燃烧。 谢谢你的帮助
以javascript格式输入dput（head（data）），否则会剪切引号：
structure(list(`1` = c(0, 0, 0, 0, 1, 0), `2` = c(0, 0, 0, 0,
0, 0), `3` = c(1, 1, 1, 1, 0, 1), `4` = structure(c(1L, 2L, 2L,
2L, 2L, 2L), .Label = c("2012", "2013", "2014", "2015", "2016",
"2017", "2018"), class = "factor"), `5` = structure(c(3L, 10L,
10L, 10L, 11L, 6L), .Label = c("1", "2", "3", "4", "5", "6",
"7", "8", "9", "10", "11", "12"), class = "factor"), `6` = structure(c(3L,
3L, 3L, 4L, 1L, 3L), .Label = c("1", "2", "3", "4", "5"), class = "factor"),
`7` = structure(c(4L, 1L, 3L, 4L, 6L, 4L), .Label = c("1",
"2", "3", "4", "5", "6", "7"), class = "factor"), `8` = structure(c(2L,
11L, 2L, 14L, 14L, 17L), .Label = c("11437", "12909", "40268",
"41238", "50836", "53001", "61709", "63415", "63567", "70304",
"71021", "81235", "1054443", "1065956", "1145941", "1186771",
"1189641", "1225376", "1281473", "1281531", "1281596", "1281654",
"1281768", "1281853", "1282081", "1282376", "1282425", "1282651",
"1282670", "1285816", "1297919", "1308960", "1311044", "1316212",
"1316362", "1325671", "1325680", "1325901", "1325910", "1334101",
"1338894", "1352983", "1362135", "1380554", "1380708", "1381162",
"1386511", "1401174", "1408423", "1408591", "1440882", "1446908",
"1449593", "1452093", "1463465", "1471795", "1472159", "1472195",
"1472888", "1484790", "1495375", "1499622", "1506430", "1513572",
"1531186", "1533126", "1535008", "1543251", "1595502"), class = "factor"),
`9` = structure(c(22L, 8L, 8L, 22L, 8L, 17L), .Label = c("6",
"17", "22", "27", "30", "37", "43", "48", "57", "58", "66",
"71", "92", "99", "103", "109", "182", "362", "556", "742",
"746", "747", "811", "849", "940", "944", "957", "959", "963",
"969", "972", "975", "980", "982", "985", "990", "999", "1023",
"1029", "1034", "1283", "9999"), class = "factor"), `10` = structure(c(13L,
13L, 13L, 19L, 19L, 14L), .Label = c("27", "30", "49", "50",
"51", "52", "53", "57", "58", "60", "61", "63", "73", "74",
"76", "91", "97", "9024", "9025"), class = "factor"), `11` = structure(c(3L,
3L, 3L, 3L, 3L, 4L), .Label = c("1", "2", "3", "4", "5",
"10", "12"), class = "factor"), `12` = structure(c(5L, 7L,
5L, 7L, 5L, 5L), .Label = c("10", "20", "30", "40", "50",
"60", "70", "80", "90", "100", "110", "120", "130", "140",
"150", "160", "200", "220"), class = "factor"), `13` = structure(c(12L,
6L, 12L, 10L, 9L, 8L), .Label = c("15", "15_20", "20_25",
"25_30", "30_35", "35_40", "40_45", "45_50", "50_55", "55_60",
"60_65", "65_70", "70_75", "75_80", "80_85", "85"), class = "factor"),
id = c(1L, 1L, 1L, 1L, 1L, 1L)), .Names = c("1", "2", "3",
"4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "id"), vars = c("4",
"5", "6", "7", "8"), labels = structure(list(`4` = structure(c(1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L), .Label = c("2012", "2013", "2014", "2015", "2016", "2017",
"2018"), class = "factor"), `5` = structure(c(3L, 6L, 6L, 6L,
8L, 9L, 9L, 10L, 10L, 10L, 11L, 1L, 4L, 5L, 5L, 6L, 6L, 6L, 7L,
7L, 7L, 7L, 8L, 8L, 9L, 10L, 11L, 11L, 12L, 12L, 12L, 12L, 1L,
1L, 2L, 2L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 7L, 7L, 7L, 7L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L,
10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 1L, 1L, 1L, 1L,
2L, 2L, 3L, 3L, 4L, 4L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 8L,
9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L,
11L, 11L, 12L, 12L, 12L, 12L, 12L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L), .Label = c("1", "2", "3", "4",
"5", "6", "7", "8", "9", "10", "11", "12"), class = "factor"),
`6` = structure(c(3L, 3L, 3L, 4L, 1L, 1L, 4L, 3L, 3L, 4L,
1L, 2L, 2L, 1L, 5L, 1L, 4L, 4L, 1L, 1L, 3L, 5L, 3L, 4L, 5L,
4L, 1L, 3L, 2L, 2L, 3L, 4L, 2L, 3L, 3L, 4L, 2L, 2L, 3L, 5L,
1L, 1L, 2L, 2L, 2L, 3L, 3L, 4L, 4L, 5L, 1L, 2L, 2L, 3L, 5L,
2L, 3L, 3L, 3L, 3L, 5L, 5L, 2L, 2L, 4L, 1L, 1L, 2L, 4L, 1L,
1L, 2L, 5L, 1L, 1L, 4L, 4L, 3L, 3L, 2L, 2L, 3L, 4L, 1L, 1L,
4L, 2L, 3L, 4L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 4L, 1L, 3L, 3L,
3L, 4L, 4L, 5L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 3L, 1L, 1L,
1L, 1L, 1L, 2L, 3L, 3L, 3L, 4L, 4L, 1L, 1L, 2L, 2L, 2L, 3L,
3L, 4L, 4L, 4L, 4L, 1L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 4L,
5L, 5L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L,
5L, 5L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L,
4L, 4L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 4L,
4L, 4L, 5L, 5L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L,
4L, 4L, 4L, 4L, 5L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L,
3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 1L, 2L, 2L, 2L, 3L, 3L, 3L,
3L, 4L, 4L, 4L, 5L, 5L, 5L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
5L, 5L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L,
3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 4L, 4L, 4L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 1L, 1L,
2L, 2L), .Label = c("1", "2", "3", "4", "5"), class = "factor"),
`7` = structure(c(4L, 4L, 5L, 1L, 2L, 2L, 1L, 1L, 3L, 4L,
6L, 5L, 1L, 5L, 4L, 4L, 1L, 4L, 3L, 5L, 3L, 3L, 5L, 4L, 1L,
3L, 4L, 5L, 2L, 5L, 4L, 3L, 6L, 2L, 6L, 2L, 1L, 6L, 1L, 4L,
5L, 5L, 2L, 4L, 5L, 1L, 3L, 2L, 5L, 1L, 5L, 1L, 1L, 3L, 7L,
1L, 1L, 2L, 3L, 5L, 2L, 3L, 1L, 3L, 4L, 1L, 2L, 4L, 5L, 1L,
5L, 2L, 3L, 2L, 3L, 1L, 4L, 4L, 6L, 2L, 4L, 5L, 1L, 2L, 3L,
3L, 1L, 2L, 1L, 1L, 1L, 3L, 4L, 1L, 1L, 2L, 2L, 3L, 2L, 3L,
5L, 1L, 3L, 1L, 2L, 1L, 2L, 5L, 1L, 3L, 3L, 1L, 1L, 2L, 2L,
3L, 4L, 5L, 5L, 1L, 4L, 5L, 1L, 4L, 1L, 3L, 2L, 3L, 4L, 1L,
2L, 1L, 1L, 3L, 5L, 7L, 1L, 5L, 2L, 2L, 3L, 4L, 5L, 1L, 1L,
4L, 5L, 1L, 1L, 4L, 1L, 2L, 4L, 4L, 6L, 2L, 2L, 3L, 2L, 3L,
3L, 4L, 4L, 2L, 2L, 3L, 3L, 4L, 6L, 3L, 4L, 4L, 5L, 5L, 4L,
1L, 2L, 1L, 1L, 2L, 2L, 3L, 4L, 3L, 3L, 4L, 4L, 1L, 2L, 4L,
2L, 3L, 1L, 2L, 4L, 5L, 2L, 3L, 1L, 2L, 4L, 4L, 5L, 1L, 1L,
3L, 5L, 1L, 1L, 1L, 2L, 4L, 5L, 1L, 3L, 3L, 1L, 3L, 4L, 3L,
3L, 4L, 6L, 6L, 4L, 1L, 1L, 4L, 1L, 1L, 1L, 3L, 4L, 5L, 1L,
1L, 1L, 2L, 4L, 7L, 3L, 5L, 5L, 1L, 1L, 3L, 5L, 1L, 3L, 5L,
5L, 1L, 3L, 4L, 1L, 2L, 7L, 2L, 3L, 5L, 5L, 6L, 1L, 1L, 4L,
5L, 5L, 1L, 3L, 5L, 5L, 2L, 4L, 4L, 3L, 1L, 1L, 2L, 3L, 4L,
4L, 1L, 3L, 4L, 5L, 1L, 1L, 2L, 4L, 6L, 6L, 1L, 1L, 1L, 2L,
5L, 6L, 3L, 5L, 1L, 1L, 2L, 2L, 3L, 6L, 7L, 2L, 4L, 5L, 6L,
7L, 1L, 1L, 1L, 1L, 3L, 4L, 4L, 5L, 5L, 1L, 1L, 3L, 3L, 3L,
3L, 4L, 5L, 4L, 5L, 5L, 1L, 4L, 1L, 1L, 2L, 1L, 1L, 1L, 3L,
1L, 1L, 2L, 3L, 3L, 5L, 5L, 6L, 1L, 3L, 1L, 1L, 2L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 3L, 5L,
1L, 2L), .Label = c("1", "2", "3", "4", "5", "6", "7"), class = "factor"),
`8` = structure(c(2L, 17L, 17L, 17L, 14L, 6L, 16L, 11L, 2L,
14L, 14L, 3L, 8L, 7L, 16L, 15L, 14L, 14L, 16L, 22L, 27L,
16L, 29L, 29L, 16L, 18L, 29L, 18L, 22L, 16L, 21L, 32L, 21L,
19L, 27L, 29L, 16L, 18L, 13L, 41L, 17L, 22L, 30L, 38L, 38L,
9L, 21L, 38L, 41L, 16L, 24L, 33L, 36L, 18L, 38L, 25L, 18L,
29L, 22L, 26L, 21L, 29L, 22L, 22L, 16L, 47L, 23L, 19L, 22L,
16L, 20L, 5L, 37L, 19L, 26L, 31L, 31L, 10L, 36L, 16L, 16L,
30L, 16L, 36L, 42L, 28L, 40L, 35L, 49L, 1L, 22L, 49L, 51L,
49L, 49L, 40L, 49L, 49L, 30L, 16L, 18L, 49L, 20L, 49L, 22L,
49L, 16L, 49L, 12L, 26L, 49L, 49L, 47L, 20L, 49L, 45L, 26L,
53L, 53L, 53L, 53L, 53L, 13L, 53L, 49L, 53L, 53L, 53L, 53L,
16L, 53L, 49L, 53L, 53L, 53L, 35L, 19L, 49L, 22L, 49L, 49L,
53L, 53L, 49L, 61L, 53L, 49L, 31L, 49L, 53L, 53L, 53L, 49L,
53L, 18L, 49L, 53L, 53L, 16L, 49L, 53L, 29L, 49L, 34L, 49L,
37L, 53L, 37L, 53L, 64L, 19L, 20L, 49L, 53L, 49L, 51L, 49L,
14L, 53L, 53L, 64L, 49L, 49L, 53L, 54L, 49L, 53L, 14L, 49L,
53L, 51L, 37L, 49L, 49L, 53L, 37L, 49L, 53L, 53L, 53L, 49L,
51L, 53L, 49L, 53L, 26L, 53L, 49L, 53L, 49L, 49L, 49L, 53L,
49L, 49L, 60L, 19L, 49L, 49L, 24L, 53L, 53L, 49L, 53L, 53L,
26L, 49L, 49L, 24L, 49L, 53L, 49L, 53L, 16L, 19L, 50L, 53L,
63L, 49L, 53L, 16L, 49L, 53L, 47L, 53L, 49L, 53L, 53L, 49L,
48L, 53L, 49L, 49L, 49L, 53L, 63L, 49L, 49L, 53L, 49L, 53L,
53L, 22L, 53L, 49L, 53L, 68L, 62L, 49L, 49L, 53L, 53L, 49L,
53L, 53L, 53L, 59L, 49L, 53L, 49L, 53L, 51L, 19L, 53L, 53L,
49L, 53L, 49L, 52L, 22L, 31L, 37L, 47L, 49L, 31L, 53L, 49L,
39L, 53L, 26L, 49L, 53L, 55L, 53L, 53L, 53L, 49L, 53L, 53L,
49L, 49L, 45L, 49L, 53L, 57L, 49L, 49L, 50L, 42L, 53L, 4L,
49L, 49L, 53L, 53L, 57L, 53L, 65L, 53L, 26L, 49L, 49L, 53L,
26L, 37L, 49L, 43L, 53L, 67L, 49L, 44L, 49L, 53L, 46L, 53L,
49L, 53L, 49L, 68L, 49L, 58L, 66L, 49L, 1L, 2L, 5L, 8L, 9L,
16L, 17L, 18L, 19L, 20L, 21L, 22L, 24L, 25L, 27L, 29L, 33L,
34L, 36L, 38L, 39L, 41L, 47L, 49L, 53L, 54L, 55L, 64L, 68L,
49L, 56L, 69L, 58L, 53L), .Label = c("11437", "12909", "40268",
"41238", "50836", "53001", "61709", "63415", "63567", "70304",
"71021", "81235", "1054443", "1065956", "1145941", "1186771",
"1189641", "1225376", "1281473", "1281531", "1281596", "1281654",
"1281768", "1281853", "1282081", "1282376", "1282425", "1282651",
"1282670", "1285816", "1297919", "1308960", "1311044", "1316212",
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