Plot the log-likelihood surface with respect to two parameters.
surface.msm(x, params=c(1,2), np=10, type=c("contour","filled.contour","persp","image"),
point=NULL, xrange=NULL, yrange=NULL,...)
# S3 method for msm
contour(x, ...)
# S3 method for msm
persp(x, ...)
# S3 method for msm
image(x, ...)
Output from msm, representing a fitted msm model.
Integer vector with two elements, giving the indices of
the parameters to vary. All other parameters
will be fixed. Defaults to c(1,2), representing the first two
log transition intensities. See the fixedpars argument to
msm for a definition of these indices.
Number of grid points to use in each direction, by default
10. An np x np grid will be used to evaluate the likelihood
surface. If 100 likelihood function evaluations is slow, then reduce this.
Character string specifying the type of plot to produce.
"contour" | Contour plot, using the R function
contour. |
"filled.contour" | Solid-color contour plot, using the R function filled.contour. |
"persp" | Perspective plot, using the R function persp. |
"image" | Grid color plot, using the R function image. |
Vector of length n, where n is the number
of parameters in the model, including the parameters that will be
varied here. This specifies the point at which to fix the likelihood. By default, this
is the maximum likelihood estimates stored in the fitted model
x, x$estimates.
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.
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.
C. H. Jackson chris.jackson@mrc-bsu.cam.ac.uk
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.
msm, contour,
filled.contour, persp,
image.