我正在尝试了解predict

如何解决我正在尝试了解predict

我试图理解R中的predict（）操作。如果我运行这组R代码：

growth <- c(12,10,8,11,6,7,2,3,3)
tannin <- c(0,1,4,5,8)
plot(growth,tannin,pch = 20,col = "blue")
model <- lm(growth ~ tannin)
new.d <- data.frame(tannin = seq(0,0.5))
mod2 <- predict(model,newdata = new.d,se.fit = T,interval = "confidence",level = 0.95)
col <- c("red","green","green")
plot(tannin,growth,col = "blue")
matlines(new.d$tannin,mod2$fit[,1:3],col = col,lty =2)

我得到了数据的散点图和一些不错的置信区间线

但是如果我运行这组R代码：

y.hat <- c(973.6536,1620.5231,882.3643,1529.2338,1266.6586,1281.8735,1205.7990,928.0090,1574.8784,1297.0883,1190.5841,1251.4437,1187.5412,1305.3495)
gain <- c(1004,1636,852,1506,1272,1270,1269,903,1555,1260,1146,1276,1225,1321)
plot(y.hat,gain,col = "blue")
model.2 <- lm(gain ~ y.hat)
new.d.2 <- data.frame(gain = seq(800,1700,length.out = 14))
mod.3 <- predict(model.2,newdata = new.d.2,level = 0.95)
matlines(new.d.2$gain,mod.3$fit[,lty = 2)

散点图是正常的，但置信度线都很奇怪。

请帮助我理解原因。

感谢柯克

解决方法

正如@MrFlick所指出的那样，您的预测函数很可能是错误的...

如果您要基于“增益”来预测值，由于增益是您在predict（）函数中的输入，因此您的lm函数应该为lm(y.hat ~ gain)，并且您的图形看起来会很好。

col <- c("red","green","green")
y.hat <- c(973.6536,1620.5231,882.3643,1529.2338,1266.6586,1281.8735,1205.7990,928.0090,1574.8784,1297.0883,1190.5841,1251.4437,1187.5412,1305.3495)
gain <- c(1004,1636,852,1506,1272,1270,1269,903,1555,1260,1146,1276,1225,1321)

model.2 <- lm(y.hat ~ gain)

new.d.2 <- data.frame(gain = seq(800,1700,length.out = 14))
mod.3 <- predict(model.2,newdata = new.d.2,se.fit = T,interval = "confidence",level = 0.95)

plot(gain,y.hat,pch = 20,col = "blue")
matlines(new.d.2$gain,mod.3$fit[,1:3],col = col,lty = 2)

^{由reprex package（v0.3.0）于2020-08-18创建}