# residuals: Residuals of GEL or GMM In gmm: Generalized Method of Moments and Generalized Empirical Likelihood

## Description

Method to extract the residuals of the model estimated by gmm or gel.

## Usage

 1 2 3 4 ## S3 method for class 'gel' residuals(object, ...) ## S3 method for class 'gmm' residuals(object, ...) 

## Arguments

 object An object of class gmm or gel returned by the function gmm or gel ... Other arguments when residuals is applied to an other classe object

## Value

It returns the matrix of residuals (y-\hat{y}) in g=y~x as it is done by residuals.lm.

## Examples

  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.