Plot a two-dimensional fit-statistic contour plot of the last steppar run.
XSPEC> plot contour [<min fit stat> [<# levels> [<levels>]]]
where <min fit stat> is the minimum fit statistic relative to which the delta fit statistic is calculated, <# levels> is the number of contour levels to use and <levels> := <level1> ... <levelN> are the contour levels in the delta fit statistic.
contour will plot the fit statistic grid calculated by the last steppar command (which should have gridded on two parameters). A small plus sign (``+'') will be drawn on the plot at the parameter values corresponding to the minimum found by the most recent fit.
The fit statistic confidence contours are often drawn based on a relatively small grid (i.e., 5x5). To fully understand what these plots are telling you, it is useful to know a couple of points concerning how the software chooses the location of the contour lines.
The contour plot is drawn based only on the information contained in the sample grid. For example, if the minimum fit statistic occurs when parameter 1 equal 2.25 and you use steppar 1 1.0 5.0 4, then the grid values closest to the minimum are 2.0 and 3.0. This could mean that there are no grid points where delta-fit statistic is less than your lowest level (which defaults to 1.0). As a result, the lowest contour will not be drawn. This effect can be minimized by always selecting a steppar range that causes XSPEC to step very close to the true minima. For the above example, using steppar 1 1.25 5.25 4, would have been a better selection.
The location of a contour line between grid points is designated using a linear interpolation. Since the fit statistic surface is often quadratic, a linear interpolation will result in the lines being drawn inside the true location of the contour. The combination of this and the previous effect sometimes will result in the minimum found by the fit command lying outside the region enclosed by the lowest contour level.