gmm (version 1.6-2)

plot: Plot Diagnostics for gel and gmm objects

Description

It is a plot method for gel or gmm objects.

Usage

# S3 method for 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 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"))

Arguments

x

gel or gmm object, typically result of gel or gmm.

which

if a subset of the plots is required, specify a subset of the numbers 1:4 for gel or 1:3 for gmm.

main

Vector of titles for each plot.

panel

panel function. The useful alternative to points, panel.smooth can be chosen by add.smooth = TRUE.

ask

logical; if TRUE, the user is asked before each plot, see par(ask=.).

…

other parameters to be passed through to plotting functions.

add.smooth

logical indicating if a smoother should be added to most plots; see also panel above.

Details

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 \(1/T\).

Examples

# NOT RUN {
# 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)
# }