```
## Willam H. Greene, Econometric Analysis, 2nd Ed.
## Chapter 15
## load data set, p. 411, Table 15.1
data(Investment)
## fit linear model, p. 412, Table 15.2
fm <- lm(RealInv ~ RealGNP + RealInt, data = Investment)
summary(fm)
## visualize residuals, p. 412, Figure 15.1
plot(ts(residuals(fm), start = 1964),
type = "b", pch = 19, ylim = c(-35, 35), ylab = "Residuals")
sigma <- sqrt(sum(residuals(fm)^2)/fm$df.residual) ## maybe used df = 26 instead of 16 ??
abline(h = c(-2, 0, 2) * sigma, lty = 2)
if(require(lmtest)) {
## Newey-West covariances, Example 15.3
coeftest(fm, vcov = NeweyWest(fm, lag = 4))
## Note, that the following is equivalent:
coeftest(fm, vcov = kernHAC(fm, kernel = "Bartlett", bw = 5, prewhite = FALSE, adjust = FALSE))
## Durbin-Watson test, p. 424, Example 15.4
dwtest(fm)
## Breusch-Godfrey test, p. 427, Example 15.6
bgtest(fm, order = 4)
}
## visualize fitted series
plot(Investment[, "RealInv"], type = "b", pch = 19, ylab = "Real investment")
lines(ts(fitted(fm), start = 1964), col = 4)
## 3-d visualization of fitted model
if(require(scatterplot3d)) {
s3d <- scatterplot3d(Investment[,c(5,7,6)],
type = "b", angle = 65, scale.y = 1, pch = 16)
s3d$plane3d(fm, lty.box = "solid", col = 4)
}
```

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