# plot: Plot Diagnostics for gel and gmm objects In gmm: Generalized Method of Moments and Generalized Empirical Likelihood

## Description

It is a plot method for gel or gmm objects.

## Usage

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 ## 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")) 

## 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

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 # 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) 

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

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