area.mse {pgs} | R Documentation |
Compute a MSE approximation for area predictors. The structure of interest is an isotropic planar random compact set. The sampling device is a uniform random lattice of figures (point patterns, line segments, quadrats...). The approximation depends only on sampling parameters and on the mean perimeter (to be provided) of the structure.
area.mse(x, B = 1, L = 3)
x |
a lattice of figures, object of class FigLat-class . |
B |
the mean perimeter. Default: 1. |
L |
an integer, the criterion for stopping summation of the
Epstein zeta function. Argument of the function Ezeta . Default: 3. |
The MSE approximation as a numeric.
Kieu, K. and Mora, M. (2006). Precision of stereological planar area predictors. J. Microsc., 222(3), 201-211.
# Sampling by a unit hexagonal point lattice area.mse(PPHexLat2()) # Sampling by a unit square point lattice area.mse(PPRectLat2()) # Sampling by a lattice of point patterns area.mse(PPRectLat2(n=5,hp=0.1)) # Sampling by quadrats (may be slow) ## Not run: area.mse(QRectLat2(hq=0.5,vq=0.7)) # Sampling by a square lattice of segments (may be slow) ## Not run: area.mse(SRectLat2(end=c(0.5,0.1)) # Sampling by an hexagonal lattice of segments (may be slow) ## Not run: area.mse(SHexLat2(end=c(0.2,0.15)))