如何在R中重現預測函數的結果

Question

假設我在 R 中訓練了一個模型。

model <- lm(as.formula(paste((model_Data)[2],"~",paste((model_Data)[c(4,5,6,7,8,9,10,11,12,13,15,16,17,18,20,21,22,63,79,90,91,109,125,132,155,175,197,202,210,251,252,279,287,292,300,313,318)],collapse="+"),sep="")),data=model_Data)

然后我使用該模型來預測未知數。

prediction <- predict(model,unknown[1,])
1 
8.037219

而不是使用預測讓我們拉出系數並手動完成。

model$coefficients
9.250265284
0.054054202
0.052738367
-0.55119556
0.019686046
0.392728331
0.794558094
0.200555755
-0.63218309
0.050404541
0.089660195
-0.04889444
-0.24645514
0.225817891
-0.10411162
0.108317865
0.004281512
0.219695437
0.037514904
-0.00914805
0.077885231
0.656321472
-0.05436867
0.033296525
0.072551915
-0.11498145
-0.03414029
0.081145352
0.11187141
0.690106624
NA
-0.11112986
-0.18002883
0.006238802
0.058387332
-0.04469568
-0.02520228
0.121577926

看起來模型找不到其中一個變量的系數。

這是我們未知的自變量。

2.048475484
1.747222331
-1.240658767
-1.26971135
-0.61858754
-1.186401425
-1.196781456
-0.437969964
-1.37330171
-1.392555895
-0.147275619
0.315190159
0.544014105
-1.137999082
0.464498153
-1.825631473
-1.824991143
0.61730876
-1.311527708
-0.457725059
-0.455920549
-0.196326975
0.636723746
0.128123676
-0.0064055
-0.788435688
-0.493452602
-0.563353694
-0.441559371
-1.083489708
-0.882784077
-0.567873188
1.068504735
1.364721122
0.294178454
2.302875604
-0.998685333

如果我將每個自變量乘以其系數並加上截距，未知數的預測值為 8.450137349

預測函數給了我們 8.037219，手動計算給了 8.450137349。 預測函數中發生了什么導致它預測出與手動計算不同的值？ 必須做什么才能使值匹配？

Answer 1

使用以下代碼時，我更接近predict答案：

b <- c(9.250265284, 0.054054202, 0.052738367, -0.55119556, 0.019686046, 0.392728331, 0.794558094, 0.200555755, -0.63218309, 0.050404541, 0.089660195, -0.04889444, -0.24645514, 0.225817891, -0.10411162, 0.108317865, 0.004281512, 0.219695437, 0.037514904, -0.00914805, 0.077885231, 0.656321472, -0.05436867, 0.033296525, 0.072551915, -0.11498145, -0.03414029, 0.081145352, 0.11187141, 0.690106624, NA, -0.11112986, -0.18002883, 0.006238802, 0.058387332, -0.04469568, -0.02520228, 0.121577926)
x <- c(1, 2.048475484, 1.747222331, -1.240658767, -1.26971135, -0.61858754, -1.186401425, -1.196781456, -0.437969964, -1.37330171, -1.392555895, -0.147275619, 0.315190159, 0.544014105, -1.137999082, 0.464498153, -1.825631473, -1.824991143, 0.61730876, -1.311527708, -0.457725059, -0.455920549, -0.196326975, 0.636723746, 0.128123676, -0.0064055, -0.788435688, -0.493452602, -0.563353694, -0.441559371, -1.083489708, -0.882784077, -0.567873188, 1.068504735, 1.364721122, 0.294178454, 2.302875604, -0.998685333)

# remove the missing value in `b` and the corresponding value in `x`
x <- x[-31]
b <- b[-31]
x %*% b
#          [,1]
# [1,] 8.036963