Description Usage Arguments Details Author(s) See Also

Plot the log-likelihood surface with respect to two parameters.

1 2 3 4 5 6 7 8 |

`x` |
Output from | |||||||||

`params` |
Integer vector with two elements, giving the indices of
the parameters to vary. All other parameters
will be fixed. Defaults to | |||||||||

`np` |
Number of grid points to use in each direction, by default
10. An | |||||||||

`type` |
Character string specifying the type of plot to produce.
| |||||||||

`point` |
Vector of length | |||||||||

`xrange` |
Range to plot for the first varied parameter. Defaults to plus and minus two standard errors, obtained from the Hessian at the maximum likelihood estimate. | |||||||||

`yrange` |
Range to plot for the second varied parameter. Defaults to plus and minus two standard errors, obtained from the Hessian at the maximum likelihood estimate. | |||||||||

`...` |
Further arguments to be passed to the plotting function. |

Draws a contour or perspective plot. Useful for diagnosing
irregularities in the likelihood surface. If you want to use these
plots before running the maximum likelihood estimation, then just run
`msm`

with all estimates fixed at their initial values.

`contour.msm`

just calls surface.msm with `type = "contour"`

.

`persp.msm`

just calls surface.msm with `type = "persp"`

.

`image.msm`

just calls surface.msm with `type = "image"`

.

As these three functions are methods of the generic functions
`contour`

, `persp`

and `image`

, they
can be invoked as `contour(x)`

, `persp(x)`

or
`image(x)`

, where `x`

is a fitted `msm`

object.

C. H. Jackson [email protected]

`msm`

, `contour`

,
`filled.contour`

, `persp`

,
`image`

.

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