Plot Diagnostics for gel and gmm objects
It is a plot method for gel or gmm objects.
## S3 method for class 'gel'
plot(x, which = c(1L:4),
main = list("Residuals vs Fitted values", "Normal Q-Q",
"Response variable and fitted values","Implied probabilities"),
panel = if(add.smooth) panel.smooth else points,
ask = prod(par("mfcol")) < length(which) && dev.interactive(), ...,
add.smooth = getOption("add.smooth"))
## S3 method for class 'gmm'
plot(x, which = c(1L:3),
main = list("Residuals vs Fitted values", "Normal Q-Q",
"Response variable and fitted values"),
panel = if(add.smooth) panel.smooth else points,
ask = prod(par("mfcol")) < length(which) && dev.interactive(), ...,
add.smooth = getOption("add.smooth"))x |
|
which |
if a subset of the plots is required, specify a subset of
the numbers |
main |
Vector of titles for each plot. |
panel |
panel function. The useful alternative to
|
ask |
logical; if |
... |
other parameters to be passed through to plotting functions. |
add.smooth |
logical indicating if a smoother should be added to
most plots; see also |
It is a beta version of a plot method for gel objects. It is a modified version of plot.lm. For now, it is available only for linear models expressed as a formula. Any suggestions are welcome regarding plots or options to include.
The first two plots are the same as the ones provided by plot.lm, the third is the dependant variable y with its mean \hat{y} (the fitted values) and the last plots the implied probabilities with the empirical density 1/T.
# GEL # n = 500 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 <- 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 t0 <- c(0,.5,.5) res <- gel(g, x, t0) plot(res, which = 3) plot(res, which = 4) # GMM # res <- gmm(g, x) plot(res, which = 3)
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