R: Plot F Statistics

plot.Fstats {strucchange} | R Documentation

## Plot F Statistics

### Description

Plotting method for objects of class `"Fstats"`

### Usage

    ## S3 method for class 'Fstats'
    plot(x, pval = FALSE, asymptotic = FALSE, alpha = 0.05,
        boundary = TRUE, aveF = FALSE, xlab = "Time", ylab = NULL,
        ylim = NULL, ...)

### Arguments

`x` | an object of class `"Fstats"`.
`pval` | logical. If set to `TRUE` the corresponding p values instead of the original F statistics will be plotted.
`asymptotic` | logical. If set to `TRUE` the asymptotic (chi-square) distribution instead of the exact (F) distribution will be used to compute the p values (only if `pval` is `TRUE`).
`alpha` | numeric from interval (0,1) indicating the confidence level for which the boundary of the supF test will be computed.
`boundary` | logical. If set to `FALSE` the boundary will be computed but not plotted.
`aveF` | logical. If set to `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.
`xlab, ylab, ylim, ...` | high-level `plot` function parameters.

### References

Andrews D.W.K. (1993), Tests for parameter instability and structural change with unknown change point, Econometrica, 61, 821-856.

Hansen B. (1992), Tests for parameter instability in regressions with I(1) processes, Journal of Business & Economic Statistics, 10, 321-335.

Hansen B. (1997), Approximate asymptotic p values for structural-change tests, Journal of Business & Economic Statistics, 15, 60-67.

### See Also

`Fstats`, `boundary.Fstats`, `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")

[Package strucchange version 1.5-2 Index]