将线性模型系数提取到循环内的向量中

问题描述

我正在尝试使用R中的循环创建200个线性模型系数的样本.最终，我想要一个包含系数的向量.

I am trying to create sample of 200 linear model coefficients using a loop in R. As an end result, I want a vector containing the coefficients.

for (i in 1:200) {
  smpl_5 <- population[sample(1:1000, 5), ]
  model_5 <- summary(lm(y~x, data=smpl_5))
}

我可以很容易地提取系数，但是在将其输出到循环内的向量时遇到了麻烦.有什么建议吗?

I can extract the coefficients easy enough, but I am having trouble outputting them into a vector within the loop. Any Suggestions?

推荐答案

您可以根据需要使用replicate.在您的情况下，由于所有模型的系数数均相同，因此它将返回一个数组，如下例所示:

You can use replicate for this if you like. In your case, because the number of coefficients is identical for all models, it'll return an array as shown in the example below:

d <- data.frame(x=runif(1000))
d$y <- d$x * 0.123 + rnorm(1000, 0, 0.01)
coefs <- replicate(3, {
  xy <- d[sample(nrow(d), 100), ]
  coef(summary(lm(y~x, data=xy)))
})

coefs

# , , 1
#
#                Estimate  Std. Error    t value     Pr(>|t|)
# (Intercept) 0.001361961 0.002091297  0.6512516 5.164083e-01
# x           0.121142447 0.003624717 33.4212114 2.235307e-55
#
# , , 2
#
#                Estimate  Std. Error  t value     Pr(>|t|)
# (Intercept) 0.003213314 0.001967050  1.63357 1.055579e-01
# x           0.118026828 0.003332906 35.41259 1.182027e-57
#
# , , 3
#
#                Estimate  Std. Error   t value     Pr(>|t|)
# (Intercept) 0.003366678 0.001990226  1.691606 9.389883e-02
# x           0.119408470 0.003370190 35.430783 1.128070e-57

使用常规数组索引访问特定元素，例如:

Access particular elements with normal array indexing, e.g.:

coefs[, , 1] # return the coefs for the first model

#                Estimate  Std. Error    t value     Pr(>|t|)
# (Intercept) 0.001361961 0.002091297  0.6512516 5.164083e-01
# x           0.121142447 0.003624717 33.4212114 2.235307e-55

因此，对于您的问题，您可以使用:

So, for your problem, you could use:

replicate(200, {
  smpl_5 <- population[sample(1:1000, 5), ]
  coef(summary(lm(y~x, data=smpl_5)))
})

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