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
.