Description Usage Arguments Value Examples

Method to extract the residuals of the model estimated by `gmm`

or `gel`

.

1 2 3 4 |

`object` |
An object of class |

`...` |
Other arguments when |

It returns the matrix of residuals *(y-\hat{y})* in `g=y~x`

as it is done by `residuals.lm`

.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | ```
# GEL can deal with endogeneity problems
n = 200
phi<-c(.2,.7)
thet <- 0.2
sd <- .2
set.seed(123)
x <- matrix(arima.sim(n = n, list(order = c(2,0,1), ar = phi, ma = thet, sd = sd)), ncol = 1)
y <- x[7:n]
ym1 <- x[6:(n-1)]
ym2 <- x[5:(n-2)]
H <- cbind(x[4:(n-3)], x[3:(n-4)], x[2:(n-5)], x[1:(n-6)])
g <- y ~ ym1 + ym2
x <- H
res <- gel(g, x, c(0,.3,.6))
e <- residuals(res)
plot(e, type = 'l', main = "Residuals from an ARMA fit using GEL")
# GMM is like GLS for linear models without endogeneity problems
set.seed(345)
n = 200
phi<-c(.2,.7)
thet <- 0
sd <- .2
x <- matrix(arima.sim(n = n, list(order = c(2,0,1), ar = phi, ma = thet, sd = sd)), ncol = 1)
y <- 10 + 5*rnorm(n) + x
res <- gmm(y ~ x, x)
plot(x, residuals(res), main = "Residuals of an estimated model with GMM")
``` |

gmm documentation built on June 20, 2017, 3:01 p.m.

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