我正在使用EViews中内置的一些模型，并将其放入R中。我在复制EViews的MA函数时遇到麻烦。
我尝试使用回归残差的滞后时间，但这并不完全相同。我已经看到一些提及，这是一个ARIMA回归。是否无法通过MA回归从EViews复制lm？
例如在R中：
set.seed(2)
a = data.frame(a = 1:6,
b = runif(6, 0.0, 1.0),
c = runif(6, 0.0, 1.0))
fit_C = lm(c ~ a + b, data = a)
a$C.pred = predict.lm(fit_C, a)
a$C.resid = a$c - a$C.pred
fit_C = lm(c ~ a + b + lag(C.resid, 1), data = a)
summary(fit_C)
输出：
Call:
lm(formula = c ~ a + b + lag(C.resid, 1), data = a)
Residuals:
1 2 3 4 5 6
-1.779e-17 -1.131e-17 5.474e-17 -5.218e-18 -1.959e-17 -8.320e-19
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.327e-01 4.279e-17 1.011e+16 <2e-16 ***
a -3.998e-02 1.353e-17 -2.954e+15 <2e-16 ***
b 2.889e-01 7.278e-17 3.969e+15 <2e-16 ***
lag(C.resid, 1) 1.000e+00 8.241e-17 1.213e+16 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 4.389e-17 on 2 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 5.444e+31 on 3 and 2 DF, p-value: < 2.2e-16
在EViews中：
Dependent Variable: C01
Method: Least Squares
Date: 09/18/18 Time: 10:24
Sample: 1 6
Included observations: 6
Convergence achieved after 9 iterations
MA Backcast: 0
Variable Coefficient Std. Error t-Statistic Prob.
C 0.892941 0.147320 6.061254 0.0262
A -0.101365 0.041651 -2.433684 0.1354
B 0.063370 0.257874 0.245740 0.8288
MA(1) -0.982901 0.058536 -16.79134 0.0035
R-squared 0.933603 Mean dependent var 0.462030
Adjusted R-squared 0.834008 S.D. dependent var 0.250812
S.E. of regression 0.102186 Akaike info criterion -1.489321
Sum squared resid 0.020884 Schwarz criterion -1.628148
Log likelihood 8.467963 Hannan-Quinn criter. -2.045057
F-statistic 9.373951 Durbin-Watson stat 2.907407
Prob(F-statistic) 0.097923
Inverted MA Roots .98
如何在R中复制MA(1)变量？