Construct a (smooth) marginal z density approximation from a model information list
getMarginalZ(
info,
method = c("linear", "spline", "logspline", "normalspline", "normal"),
verbose = FALSE,
plot = FALSE
)
the model information list
method for approximating the marginal density:
Linearly interpolate the points.
The saved points of the unnormalized density approximation are joined by a “monotonic” spline. The density is smoothed out to zero at the tails. Since the spline might be slightly negative for extreme values, the positive part is returned.
The saved points of the log unnormalized density approximation are joined by a “monotonic” spline, which is then exponentiated.
A “monotonic” spline is fitted to the differences of the saved log density values and the log normal approximation. The resulting spline function is exponentiated and then multiplied with the normal density.
Just take the normal approximation.
Echo the chosen method? (not default)
produce plots of the different approximation steps? (not default)
a list with the log of the normalized density approximation (“logDens”) and the random number generator (“gen”).