请对以下问题写出R代码:①做出50×30的随机数据和30个变量;②做出三组不同数的关于①的线性模型;③计算每组的CV值;④以par(3,2)的布局,画出每组的以lambda为横坐标,分别以CV error和Prediction error为纵坐标的图
时间: 2024-02-24 14:00:07 浏览: 16
好的,以下是R代码:
①生成随机数据:
```
set.seed(123)
data <- matrix(rnorm(50*30), nrow = 50, ncol = 30)
```
②生成三组不同的线性模型:
```
library(glmnet)
x <- data[,1:29]
y <- data[,30]
fit1 <- cv.glmnet(x, y, alpha = 1, nfolds = 10)
fit2 <- cv.glmnet(x, y+rnorm(50), alpha = 1, nfolds = 10)
fit3 <- cv.glmnet(x, y+rnorm(50,mean=2), alpha = 1, nfolds = 10)
```
③计算每组的CV值:
```
cv1 <- min(fit1$cvm)
cv2 <- min(fit2$cvm)
cv3 <- min(fit3$cvm)
```
④画出每组的图:
```
par(mfrow=c(3,2))
plot(fit1$lambda, fit1$cvm, type="l", xlab="lambda", ylab="CV error", main="Model 1")
plot(fit1$lambda, fit1$glmnet.fit$dev.ratio, type="l", xlab="lambda", ylab="Prediction error", main="Model 1")
plot(fit2$lambda, fit2$cvm, type="l", xlab="lambda", ylab="CV error", main="Model 2")
plot(fit2$lambda, fit2$glmnet.fit$dev.ratio, type="l", xlab="lambda", ylab="Prediction error", main="Model 2")
plot(fit3$lambda, fit3$cvm, type="l", xlab="lambda", ylab="CV error", main="Model 3")
plot(fit3$lambda, fit3$glmnet.fit$dev.ratio, type="l", xlab="lambda", ylab="Prediction error", main="Model 3")
```