data.table vs plyr回归输出 [英] data.table vs plyr regression output

问题描述

data.table包在速度方面非常有帮助。但我有麻烦实际使用的线性回归的输出。有一个简单的方法来获得data.table输出是漂亮/有用的，从plyr包吗？下面是一个例子。谢谢！

The data.table package is very helpful in terms of speed. But I am having trouble actually using the output from a linear regression. Is there an easy way to get the data.table output to be as pretty/useful as that from the plyr package? Below is an example. Thank you!

library('data.table');
library('plyr');

REG <- data.table(ID=c(rep('Frank',5),rep('Tony',5),rep('Ed',5)), y=rnorm(15), x=rnorm(15), z=rnorm(15));
REG;

ddply(REG, .(ID), function(x) coef(lm(y ~ x + z, data=x)));

REG[, coef(lm(y ~ x + z)), by=ID];

data.table系数估计值输出在一列，而ply​​r / ddply系数估计值输出在多个和很好地标记的列。

The data.table coefficient estimates are output in a single column whereas the plyr/ddply coefficient estimates are output in multiple and nicely labeled columns.

我知道我可以运行回归三次与data.table，但似乎真的效率低下。我可能错了。

I know I can run the regression three times with data.table but that seems really inefficient. I could be wrong, though.

REG[, Intercept=coef(lm(y ~ x + z))[1],
      x        =coef(lm(y ~ x + z))[2],
      z        =coef(lm(y ~ x + z))[3], by=ID];

推荐答案

尝试：

> REG[, as.list(coef(lm(y ~ x + z))), by=ID];
        ID (Intercept)           x         z
[1,] Frank  -0.2928611  0.07215896  1.835106
[2,]  Tony   0.9120795 -1.11153056  2.041260
[3,]    Ed   1.0498359  5.77131778 -1.253741

我有一个尴尬的感觉，这个问题是不到一个星期前被问的，但我不认为我达到这种方法，当我试一试，我不记得比任何答案是这个契约。

I have the nagging feeling that this question was asked less than a week ago, but I don't think I arrived at this approach when I tried it and I don't remember than any answer was this compact.

哦，有r-help的..马修可以评论这个的合法性，如果他想。我想消息是函数返回列表将不会有维度删除。有趣的是使用列表（coef（lm（...））没有以我们希望的方式成功。

Oh, there it is .. on r-help. Matthew can comment on the rightfulness of this if he wants. I guess the message is that functions returning lists will not have dimensions dropped. The interesting thing was the using list(coef(lm(...)) did not succeed in the manner we hoped.

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