dnestlog.grid {BMAmevt} | R Documentation |
The two functions compute respectively the NL and PB spectral densities, in the three-dimensional case, on a discretization grid. A plot is issued (optional).
dnestlog.grid(par, npoints = 50, eps = 0.001, equi = TRUE, displ = TRUE, invisible = TRUE, ...) dpairbeta.grid(par, npoints = 50, eps = 0.001, equi = TRUE, displ = TRUE, invisible = TRUE, ...)
par |
The parameter for the Pairwise Beta or the Nested Logistic density.
|
npoints |
The number of grid nodes on the squared grid containing the desired triangle. |
eps |
Positive number: minimum distance from any node inside the simplex to the simplex boundary |
equi |
logical. Is the simplex represented as an equilateral triangle (if |
displ |
logical. Should a plot be produced ? |
invisible |
logical. If |
... |
Additional arguments to be passed to |
A npoints*npoints
matrix containing the
considered density's values on the grid.
The row (resp. column) indices increase
with the first (resp. second) coordinate on the simplex.
If equi==TRUE
, the density is relative to the Hausdorff
measure on the simplex itself: the values obtained with
equi = FALSE
are thus divided by
√ 3.
dpairbeta.grid(par=c( 0.8, 8, 5, 2), npoints=70, eps = 1e-3, equi = TRUE, displ = TRUE, invisible=TRUE) ## or ... Dens <- dpairbeta.grid(par=c(0.8, 8, 5, 2), npoints=70, eps = 1e-3, equi = TRUE, displ = FALSE) Grid=discretize(npoints=70,eps=1e-3,equi=TRUE) dev.new() image(Grid$X, Grid$Y, Dens) contour(Grid$X, Grid$Y, Dens, add=TRUE) add.frame(equi=TRUE, npoints=70, axes=FALSE)