`mba.surf`

returns a surface approximated from a
bivariate scatter of data points using multilevel B-splines.
`mba.surf(xyz, no.X, no.Y, n = 1, m = 1, h = 8, extend=FALSE, sp=FALSE, ...)`

xyz

a $n x 3$ matrix or data frame, where $n$ is
the number of observed points. The three columns correspond to point x, y, and z
coordinates. The z value is the response at the given x, y
coordinates.

no.X

resolution of the approximated surface along the x axis.

no.Y

resolution of the approximated surface along the y axis.

n

initial size of the spline space in the hierarchical
construction along the x axis. If the rectangular domain is a
square, n = m = 1 is recommended. If the x axis is k times the length
of the y axis, n = 1, m = k is recommended. The default is n = 1.

m

initial size of the spline space in the hierarchical
construction along the y axis. If the y axis is k times the length
of the x axis, m = 1, n = k is recommended. The default is m = 1.

h

Number of levels in the hierarchical construction. If, e.g.,
n = m = 1 and h = 8, the resulting spline surface has a coefficient
grid of size $2^h$ + 3 = 259 in each direction of the
spline surface. See references for additional information.

extend

if FALSE, a convex hull is computed for the input points
and all matrix elements in z that have centers outside of this
polygon are set to

`NA`

; otherwise, all elements in z are given an
estimated z value. sp

if TRUE, the resulting surface is returned as a

`SpatialPixelsDataFrame`

object; otherwise, the surface is in
`image`

format....

`b.box`

is an optional vector to sets the bounding
box. The vector's elements are minimum x, maximum x, minimum y, and maximum
y, respectively. -
List with 8 component:
- xyz.est
- a list that contains vectors x, y and the $no.X x no.Y$ matrix z of estimated z-values.
- no.X
`no.X`

from arguments.- no.Y
`no.Y`

from arguments.- n
`n`

from arguments.- m
`m`

from arguments.- h
`h`

from arguments.- extend
`extend`

from arguments.- sp
`sp`

from arguments.- b.box
`b.box`

defines the bounding box over which z is estimated.

`mba.points`

## Not run: # data(LIDAR) # # mba.int <- mba.surf(LIDAR, 300, 300, extend=TRUE)$xyz.est # # ##Image plot # image(mba.int, xaxs="r", yaxs="r") # # ##Perspective plot # persp(mba.int, theta = 135, phi = 30, col = "green3", scale = FALSE, # ltheta = -120, shade = 0.75, expand = 10, border = NA, box = FALSE) # # ##For a good time I recommend using rgl # library(rgl) # # ex <- 10 # x <- mba.int[[1]] # y <- mba.int[[2]] # z <- ex*mba.int[[3]] # zlim <- range(z) # zlen <- zlim[2] - zlim[1] + 1 # colorlut <- heat.colors(as.integer(zlen)) # col <- colorlut[ z-zlim[1]+1 ] # # open3d() # surface3d(x, y, z, color=col, back="lines") # ## End(Not run)