## File: plot.Fstats.Rd

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strucchange 1.5-1-2
 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960 \name{plot.Fstats} \alias{plot.Fstats} \alias{lines.Fstats} \title{Plot F Statistics} \description{Plotting method for objects of class \code{"Fstats"}} \usage{ \method{plot}{Fstats}(x, pval = FALSE, asymptotic = FALSE, alpha = 0.05, boundary = TRUE, aveF = FALSE, xlab = "Time", ylab = NULL, ylim = NULL, ...) } \arguments{ \item{x}{an object of class \code{"Fstats"}.} \item{pval}{logical. If set to \code{TRUE} the corresponding p values instead of the original F statistics will be plotted.} \item{asymptotic}{logical. If set to \code{TRUE} the asymptotic (chi-square) distribution instead of the exact (F) distribution will be used to compute the p values (only if \code{pval} is \code{TRUE}).} \item{alpha}{numeric from interval (0,1) indicating the confidence level for which the boundary of the supF test will be computed.} \item{boundary}{logical. If set to \code{FALSE} the boundary will be computed but not plotted.} \item{aveF}{logical. If set to \code{TRUE} the boundary of the aveF test will be plotted. As this is a boundary for the mean of the F statistics rather than for the F statistics themselves a dashed line for the mean of the F statistics will also be plotted.} \item{xlab, ylab, ylim, ...}{high-level \code{\link{plot}} function parameters.}} \references{ Andrews D.W.K. (1993), Tests for parameter instability and structural change with unknown change point, \emph{Econometrica}, \bold{61}, 821-856. Hansen B. (1992), Tests for parameter instability in regressions with I(1) processes, \emph{Journal of Business & Economic Statistics}, \bold{10}, 321-335. Hansen B. (1997), Approximate asymptotic p values for structural-change tests, \emph{Journal of Business & Economic Statistics}, \bold{15}, 60-67. } \seealso{\code{\link{Fstats}}, \code{\link{boundary.Fstats}}, \code{\link{sctest.Fstats}}} \examples{ ## Load dataset "nhtemp" with average yearly temperatures in New Haven data("nhtemp") ## plot the data plot(nhtemp) ## test the model null hypothesis that the average temperature remains ## constant over the years for potential break points between 1941 ## (corresponds to from = 0.5) and 1962 (corresponds to to = 0.85) ## compute F statistics fs <- Fstats(nhtemp ~ 1, from = 0.5, to = 0.85) ## plot the F statistics plot(fs, alpha = 0.01) ## and the corresponding p values plot(fs, pval = TRUE, alpha = 0.01) ## perform the aveF test sctest(fs, type = "aveF") } \keyword{hplot}