我希望能够编写一个按组data.table
运行回归的函数,然后很好地组织结果。以下是我想要做的一个示例:
require(data.table)
dtb = data.table(y=1:10, x=10:1, z=sample(1:10), weights=1:10, thedate=1:2)
models = c("y ~ x", "y ~ z")
res = lapply(models, function(f) {dtb[,as.list(coef(lm(f, weights=weights, data=.SD))),by=thedate]})
#do more stuff with res
我想将所有这些包装成一个函数,因为#doe more stuff
可能很长。我面临的问题是如何将各种名称传递给data.table
?例如,如何传递列名weights
?我如何通过thedate
?我想象一个看起来像这样的原型:
myfun = function(dtb, models, weights, dates)
让我说清楚:将公式传递给我的函数不是问题。如果我想使用的weights
和描述日期的列名,thedate
已知,那么我的函数可能看起来像这样:
myfun = function(dtb, models) {
res = lapply(models, function(f) {dtb[,as.list(coef(lm(f, weights=weights, data=.SD))),by=thedate]})
#do more stuff with res
}
但是,与thedate
和weights
对应的列名称事先未知。我想将它们传递给我的函数:
#this will not work
myfun = function(dtb, models, w, d) {
res = lapply(models, function(f) {dtb[,as.list(coef(lm(f, weights=w, data=.SD))),by=d]})
#do more stuff with res
}
由于
答案 0 :(得分:5)
这是一个依赖于长格式数据的解决方案(这对我来说更有意义,在这个cas
library(reshape2)
dtlong <- data.table(melt(dtb, measure.var = c('x','z')))
foo <- function(f, d, by, w ){
# get the name of the w argument (weights)
w.char <- deparse(substitute(w))
# convert `list(a,b)` to `c('a','b')`
# obviously, this would have to change depending on how `by` was defined
by <- unlist(lapply(as.list(as.list(match.call())[['by']])[-1], as.character))
# create the call substituting the names as required
.c <- substitute(as.list(coef(lm(f, data = .SD, weights = w), list(w = as.name(w.char)))))
# actually perform the calculations
d[,eval(.c), by = by]
}
foo(f= y~value, d= dtlong, by = list(variable, thedate), w = weights)
variable thedate (Intercept) value
1: x 1 11.000000 -1.00000000
2: x 2 11.000000 -1.00000000
3: z 1 1.009595 0.89019190
4: z 2 7.538462 -0.03846154
答案 1 :(得分:3)
一种可能的解决方案:
fun = function(dtb, models, w_col_name, date_name) {
res = lapply(models, function(f) {dtb[,as.list(coef(lm(f, weights=eval(parse(text=w_col_name)), data=.SD))),by=eval(parse(text=paste0("list(",date_name,")")))]})
}
答案 2 :(得分:1)
你不能只添加(在匿名函数调用内):
f <- as.formula(f)
...作为dtb[,as.list(coef(lm(f, ...)
之前的单独一行?这是将字符元素转换为公式对象的常用方法。
> res = lapply(models, function(f) {f <- as.formula(f)
dtb[,as.list(coef(lm(f, weights=weights, data=.SD))),by=thedate]})
>
> str(res)
List of 2
$ :Classes ‘data.table’ and 'data.frame': 2 obs. of 3 variables:
..$ thedate : int [1:2] 1 2
..$ (Intercept): num [1:2] 11 11
..$ x : num [1:2] -1 -1
..- attr(*, ".internal.selfref")=<externalptr>
$ :Classes ‘data.table’ and 'data.frame': 2 obs. of 3 variables:
..$ thedate : int [1:2] 1 2
..$ (Intercept): num [1:2] 6.27 11.7
..$ z : num [1:2] 0.0633 -0.7995
..- attr(*, ".internal.selfref")=<externalptr>
如果您需要从组件名称构建公式的字符版本,只需使用paste
或paste0
并传递给模型字符向量。提供经测试的代码,并提供可测试示例。