如何为R中的预定义向量创建回归模型列表？
要为预定义向量创建回归模型列表，我们可以创建一个空白列表，然后使用for循环创建回归模型列表。例如，如果我们有两个向量分别表示x和y，并且我们想在x和y之间创建回归模型列表，则可以使用空白列表list()并执行for循环特定次数，如以下示例所示。
例1
x<-rnorm(20) y<-rnorm(20) List_1=list() for (i in 1:10) List_1[[i]] = lm(y~x) List_1输出结果
[[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
例子2
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输出结果
[[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