預測()-也許我不明白I 今天早些時候發(fā)帖使用predict功能。我得到了糾正，并認為我走上了正確的道路。我有一些觀察(實際值)，我有一些數(shù)據(jù)點，我想推斷或預測。我用lm為了創(chuàng)建一個模型，我嘗試使用predict作為預測器輸入的實際值。這段代碼都是從我上一篇文章中重復的，但如下所示：df <- read.table(text = '
Quarter Coupon Total
1 "Dec 06" 25027.072 132450574
2 "Dec 07" 76386.820 194154767
3 "Dec 08" 79622.147 221571135
4 "Dec 09" 74114.416 205880072
5 "Dec 10" 70993.058 188666980
6 "Jun 06" 12048.162 139137919
7 "Jun 07" 46889.369 165276325
8 "Jun 08" 84732.537 207074374
9 "Jun 09" 83240.084 221945162
10 "Jun 10" 81970.143 236954249
11 "Mar 06" 3451.248 116811392
12 "Mar 07" 34201.197 155190418
13 "Mar 08" 73232.900 212492488
14 "Mar 09" 70644.948 203663201
15 "Mar 10" 72314.945 203427892
16 "Mar 11" 88708.663 214061240
17 "Sep 06" 15027.252 121285335
18 "Sep 07" 60228.793 195428991
19 "Sep 08" 85507.062 257651399
20 "Sep 09" 77763.365 215048147
21 "Sep 10" 62259.691 168862119', header=TRUE)str(df)'data.frame': 21 obs. of 3 variables:
$ Quarter : Factor w/ 24 levels "Dec 06","Dec 07",..: 1 2 3 4 5 7 8 9 10 11 ...
$ Coupon: num 25027 76387 79622 74114 70993 ...
$ Total: num 132450574 194154767 221571135 205880072 188666980 ...代碼：model <- lm(df$Total ~ df$Coupon, data=df)> model
Call:lm(formula = df$Total ~ df$Coupon)Coefficients:(Intercept) df$Coupon
107286259 1349預測代碼(基于以前的幫助)：(這些是我想用來獲得預測值的預測值)Quarter = c("Jun 11", "Sep 11", "Dec 11")Total = c(79037022, 83100656, 104299800)Coupon = data.frame(Quarter, Total)Coupon$estimate <- predict(model, newdate = Coupon$Total)現(xiàn)在，當我運行它時，我會得到以下錯誤消息：Error in `$<-.data.frame`(`*tmp*`, "estimate", value = c(60980.3823396919, :
replacement has 21 rows, data has 3我用來建立模型的原始數(shù)據(jù)框架中有21個觀察結(jié)果。我現(xiàn)在試圖預測基于模型的3個值。我要么不真正理解這個函數(shù)，要么代碼中出現(xiàn)了錯誤。我會感謝你的幫助。謝謝
3 回答
手掌心
TA貢獻1942條經(jīng)驗 獲得超3個贊
model <- lm(Total ~ Coupon, data=df)
不 model <-lm(df$Total ~ df$Coupon, data=df).
lm(Total ~ Coupon)TotalCouponTotal = a + b*Couponab~
CouponTotal.
newdataCouponTotal
model <- lm(Coupon ~ Total, data=df)new.df <- data.frame(Total=c(79037022, 83100656, 104299800))predict(model, new.df)
阿晨1998
TA貢獻2037條經(jīng)驗 獲得超6個贊
lm(olive$Area@olive$Palmitic)anewdata<-data.frame(Palmitic=2)lm(Area@Palmitic,data=olive)
警告消息：“anewdata”有1行，但變量有X行
慕桂英546537
TA貢獻1848條經(jīng)驗 獲得超10個贊
model <- lm(Coupon ~ Total, data=df)predict(model, data.frame(Total=c(79037022, 83100656, 104299800)))
model <- lm(Coupon ~ Total, data=df) #Okmodel <- lm(df$Coupon ~ df$Total) #Ko
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