summary-methods {momentfit} | R Documentation |
summary
in Package base ~~Compute several results from a moment based model fit.
## S4 method for signature 'gmmfit' summary(object, ...) ## S4 method for signature 'gelfit' summary(object, ...) ## S4 method for signature 'sgmmfit' summary(object, ...)
object |
A fit object from the package (GMM and GEL are the only methods for now) |
... |
Other arguments to pass to |
signature(object = "gmmfit")
signature(object = "gmmfit")
signature(object = "sgmmfit")
data(simData) theta <- c(beta0=1,beta1=2) model1 <- momentModel(y~x1, ~z1+z2, data=simData) res <- gmmFit(model1) summary(res) ## Fixed and True Weights matrix ## Consider the moment of a normal distribution: ## Using the first three non centered moments g <- function(theta, x) { mu <- theta[1] sig2 <- theta[2] m1 <- x-mu m2 <- x^2-mu^2-sig2 m3 <- x^3-mu^3-3*mu*sig2 cbind(m1,m2,m3) } dg <- function(theta, x) { mu <- theta[1] sig2 <- theta[2] G <- matrix(c(-1,-2*mu,-3*mu^2-3*sig2, 0, -1, -3*mu),3,2) } x <- simData$x3 model <- momentModel(g, x, c(mu=.1, sig2=1.5), vcov="iid") res1 <- gmmFit(model) summary(res1) ## Same results (that's because the moment vcov is centered by default) W <- solve(var(cbind(x,x^2,x^3))) res2 <- gmmFit(model, weights=W) res2 ## If is therefore more efficient in this case to do the following: summary(res2, breadOnly=TRUE)