r - 有没有更短的方法可以在 lm() 公式中编写许多类似的变量？

Question

我确实有一个庞大的数据集，想做一些回归分析。

这是数据集。

#            Winst Item1 Item2 Item3 Item4 Item5  ...  Item100
# Event1 992.19788    92    91    79    36    71  ...       93
# Event2  43.43687    62    16    58    51    30  ...       71
# Event3 219.52095   NaN   NaN   NaN   NaN   NaN  ...      NaN
# Event4 874.76596    89    69    82    65    56  ...       91
# Event5 602.40975    36    37    27    94    54  ...       52

我怎样才能把下面的代码写得更短一些？

lm(Winst ~ Item1 + Item2 + Item3 + Item4 + ... + Item50, data=data1)

在数学中我们使用 sigma 符号，但在 r 中这个词有另一个含义。 sum() 都不起作用。

有哪些选项？

数据

data1 <- structure(list(Winst = c(992.197884479538, 43.4368695132434, 
219.520953251049, 874.765956075862, 602.409749291837), Item1 = c(92, 
62, NaN, 89, 36), Item2 = c(91, 16, NaN, 69, 37), Item3 = c(79, 
58, NaN, 82, 27), Item4 = c(36, 51, NaN, 65, 94), Item5 = c(71, 
30, NaN, 56, 54), Item6 = c(23, 35, NaN, 67, 59), Item7 = c(44, 
64, NaN, 9, 98), Item8 = c(70, 79, NaN, 75, 57), Item9 = c(91, 
26, NaN, 76, 29), Item10 = c(99, 74, NaN, 70, 78), Item11 = c(27, 
72, NaN, 74, 16), Item12 = c(10, 48, NaN, 2, 60), Item13 = c(54, 
95, NaN, 10, 17), Item14 = c(58, 82, NaN, 83, 61), Item15 = c(21, 
88, NaN, 1, 62), Item16 = c(61, 4, NaN, 23, 8), Item17 = c(7, 
46, NaN, 18, 20), Item18 = c(67, 24, NaN, 32, 92), Item19 = c(83, 
73, NaN, 42, 41), Item20 = c(42, 65, NaN, 51, 30), Item21 = c(77, 
49, NaN, 85, 85), Item22 = c(83, 19, NaN, 71, 50), Item23 = c(25, 
42, NaN, 20, 81), Item24 = c(74, 93, NaN, 17, 58), Item25 = c(23, 
84, NaN, 64, 7), Item26 = c(22, 43, NaN, 49, 65), Item27 = c(69, 
32, NaN, 45, 42), Item28 = c(92, 20, NaN, 33, 3), Item29 = c(32, 
55, NaN, 40, 22), Item30 = c(68, 76, NaN, 38, 46), Item31 = c(28, 
91, NaN, 80, 97), Item32 = c(100, 61, NaN, 35, 91), Item33 = c(86, 
36, NaN, 63, 69), Item34 = c(54, 60, NaN, 8, 34), Item35 = c(11, 
63, NaN, 22, 53), Item36 = c(63, 80, NaN, 26, 96), Item37 = c(41, 
66, NaN, 100, 2), Item38 = c(24, 98, NaN, 24, 47), Item39 = c(82, 
31, NaN, 97, 87), Item40 = c(34, 8, NaN, 95, 32), Item41 = c(60, 
27, NaN, 14, 68), Item42 = c(48, 44, NaN, 19, 56), Item43 = c(45, 
57, NaN, 57, 40), Item44 = c(72, 75, NaN, 28, 72), Item45 = c(11, 
12, NaN, 37, 88), Item46 = c(21, 70, NaN, 15, 5), Item47 = c(46, 
22, NaN, 92, 43), Item48 = c(68, 52, NaN, 7, 48), Item49 = c(6, 
5, NaN, 16, 49), Item50 = c(93, 71, NaN, 91, 52), Item51 = c(92, 
62, NaN, 89, 36), Item52 = c(91, 16, NaN, 69, 37), Item53 = c(79, 
58, NaN, 82, 27), Item54 = c(36, 51, NaN, 65, 94), Item55 = c(71, 
30, NaN, 56, 54), Item56 = c(23, 35, NaN, 67, 59), Item57 = c(44, 
64, NaN, 9, 98), Item58 = c(70, 79, NaN, 75, 57), Item59 = c(91, 
26, NaN, 76, 29), Item60 = c(99, 74, NaN, 70, 78), Item61 = c(27, 
72, NaN, 74, 16), Item62 = c(10, 48, NaN, 2, 60), Item63 = c(54, 
95, NaN, 10, 17), Item64 = c(58, 82, NaN, 83, 61), Item65 = c(21, 
88, NaN, 1, 62), Item66 = c(61, 4, NaN, 23, 8), Item67 = c(7, 
46, NaN, 18, 20), Item68 = c(67, 24, NaN, 32, 92), Item69 = c(83, 
73, NaN, 42, 41), Item70 = c(42, 65, NaN, 51, 30), Item71 = c(77, 
49, NaN, 85, 85), Item72 = c(83, 19, NaN, 71, 50), Item73 = c(25, 
42, NaN, 20, 81), Item74 = c(74, 93, NaN, 17, 58), Item75 = c(23, 
84, NaN, 64, 7), Item76 = c(22, 43, NaN, 49, 65), Item77 = c(69, 
32, NaN, 45, 42), Item78 = c(92, 20, NaN, 33, 3), Item79 = c(32, 
55, NaN, 40, 22), Item80 = c(68, 76, NaN, 38, 46), Item81 = c(28, 
91, NaN, 80, 97), Item82 = c(100, 61, NaN, 35, 91), Item83 = c(86, 
36, NaN, 63, 69), Item84 = c(54, 60, NaN, 8, 34), Item85 = c(11, 
63, NaN, 22, 53), Item86 = c(63, 80, NaN, 26, 96), Item87 = c(41, 
66, NaN, 100, 2), Item88 = c(24, 98, NaN, 24, 47), Item89 = c(82, 
31, NaN, 97, 87), Item90 = c(34, 8, NaN, 95, 32), Item91 = c(60, 
27, NaN, 14, 68), Item92 = c(48, 44, NaN, 19, 56), Item93 = c(45, 
57, NaN, 57, 40), Item94 = c(72, 75, NaN, 28, 72), Item95 = c(11, 
12, NaN, 37, 88), Item96 = c(21, 70, NaN, 15, 5), Item97 = c(46, 
22, NaN, 92, 43), Item98 = c(68, 52, NaN, 7, 48), Item99 = c(6, 
5, NaN, 16, 49), Item100 = c(93, 71, NaN, 91, 52)), class = "data.frame", row.names = c("Event1", 
"Event2", "Event3", "Event4", "Event5"))

Answer 1

您可以使用 reformulate 和 grep 列名称中的术语和正则表达式。

fo <- reformulate(grep('^Item([1-9]|[1-4][0-9]|50)$', names(data1), value=TRUE), 
                  'Winst')
fo
# Winst ~ Item1 + Item2 + Item3 + Item4 + Item5 + Item6 + Item7 + 
#   Item8 + Item9 + Item10 + Item11 + Item12 + Item13 + Item14 + 
#   Item15 + Item16 + Item17 + Item18 + Item19 + Item20 + Item21 + 
#   Item22 + Item23 + Item24 + Item25 + Item26 + Item27 + Item28 + 
#   Item29 + Item30 + Item31 + Item32 + Item33 + Item34 + Item35 + 
#   Item36 + Item37 + Item38 + Item39 + Item40 + Item41 + Item42 + 
#   Item43 + Item44 + Item45 + Item46 + Item47 + Item48 + Item49 + 
#   Item50

查看演示 there .

然后就是

lm(fo, data1)

或

do.call('lm', list(fo, quote(data1)))

显示“调用:”权利。