如何在 R 中為預定義的向量建立迴歸模型列表？

要為預定義的向量建立迴歸模型列表，我們可以建立一個空列表，然後使用 for 迴圈來建立迴歸模型列表。例如，如果我們有兩個向量，假設為 x 和 y，並且我們想要在 x 和 y 之間建立迴歸模型列表，那麼我們使用 list() 建立一個空列表，並按特定次數執行 for 迴圈，如下面示例所示。

示例 1

 線上演示

x<-rnorm(20)
y<-rnorm(20)
List_1=list()
for (i in 1:10) List_1[[i]] = lm(y~x)
List_1

輸出

[[1]]
Call:
lm(formula = y ~ x)
Coefficients:
(Intercept) x
   -0.1294 0.2600

[[2]]
Call:
lm(formula = y ~ x)
Coefficients:
(Intercept) x
   -0.1294 0.2600

[[3]]
Call:
lm(formula = y ~ x)
Coefficients:
(Intercept) x
   -0.1294 0.2600

[[4]]
Call:
lm(formula = y ~ x)
Coefficients:
(Intercept) x
   -0.1294 0.2600

[[5]]
Call:
lm(formula = y ~ x)
Coefficients:
(Intercept) x
   -0.1294 0.2600

[[6]]
Call:
lm(formula = y ~ x)
Coefficients:
(Intercept) x
   -0.1294 0.2600

[[7]]
Call:
lm(formula = y ~ x)
Coefficients:
(Intercept) x
   -0.1294 0.2600

[[8]]
Call:
lm(formula = y ~ x)
Coefficients:
(Intercept) x
   -0.1294 0.2600

[[9]]
Call:
lm(formula = y ~ x)
Coefficients:
(Intercept) x
   -0.1294 0.2600

[[10]]
Call:
lm(formula = y ~ x)
Coefficients:
(Intercept) x
   -0.1294 0.2600

示例 2

 線上演示

x1<-rpois(2000,1)
x2<-rpois(2000,2)
x3<-rpois(2000,2)
y1<-rpois(2000,5)
List_2=list()
for (i in 1:10) List_2[[i]] = lm(y1~x1+x2+x3)
List_2

輸出

[[1]]
Call:
lm(formula = y1 ~ x1 + x2 + x3)
Coefficients:
(Intercept) x1 x2 x3
   5.065561 -0.039094 0.006488 -0.035636

[[2]]
Call:
lm(formula = y1 ~ x1 + x2 + x3)
Coefficients:
(Intercept) x1 x2 x3
   5.065561 -0.039094 0.006488 -0.035636

[[3]]
Call:
lm(formula = y1 ~ x1 + x2 + x3)
Coefficients:
(Intercept) x1 x2 x3
   5.065561 -0.039094 0.006488 -0.035636

[[4]]
Call:
lm(formula = y1 ~ x1 + x2 + x3)
Coefficients:
(Intercept) x1 x2 x3
 5.065561 -0.039094 0.006488 -0.035636

[[5]]
Call:
lm(formula = y1 ~ x1 + x2 + x3)
Coefficients:
(Intercept) x1 x2 x3
   5.065561 -0.039094 0.006488 -0.035636

[[6]]
Call:
lm(formula = y1 ~ x1 + x2 + x3)
Coefficients:
(Intercept) x1 x2 x3
 5.065561 -0.039094 0.006488 -0.035636

[[7]]
Call:
lm(formula = y1 ~ x1 + x2 + x3)
Coefficients:
(Intercept) x1 x2 x3
 5.065561 -0.039094 0.006488 -0.035636

[[8]]
Call:
lm(formula = y1 ~ x1 + x2 + x3)
Coefficients:
(Intercept) x1 x2 x3
 5.065561 -0.039094 0.006488 -0.035636

[[9]]
Call:
lm(formula = y1 ~ x1 + x2 + x3)
Coefficients:
(Intercept) x1 x2 x3
 5.065561 -0.039094 0.006488 -0.035636

[[10]]
Call:
lm(formula = y1 ~ x1 + x2 + x3)
Coefficients:
(Intercept) x1 x2 x3
 5.065561 -0.039094 0.006488 -0.035636

更新時間：06-Mar-2021

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