spMC (version 0.2.2)

image.multi.tpfit: Images with Multidimensional Transiograms

Description

The function plots $2$-D sections of a predicted multidimensional transiograms computed through ellipsoidal interpolation.

Usage

## S3 method for class 'multi.tpfit':
image(x, mpoints, which.dire, max.dist, main,
      mar, ask = TRUE, ..., nlevels = 10, contour = TRUE)

Value

An image is produced on the current graphics device. No values are returned.

Rdversion

1.1

Details

A multidimensional transiogram is a diagram which shows the transition probabilities for a single pair of categories. It is computed for any lag vector $h$ through $$\mbox{expm} (\Vert h \Vert R),$$ where entries of $R$ are ellipsoidally interpolated (see multi.tpfit).

The exponential matrix is evaluated by the scaling and squaring algorithm.

References

Carle, S. F., Fogg, G. E. (1997) Modelling Spatial Variability with One and Multidimensional Continuous-Lag Markov Chains. Mathematical Geology, 29(7), 891-918.

Higham, N. J. (2008) Functions of Matrices: Theory and Computation. Society for Industrial and Applied Mathematics.

Sartore, L. (2010) Geostatistical models for 3-D data. M.Phil. thesis, Ca' Foscari University of Venice.

See Also

multi.tpfit, imgMultiTransiogram, image, plot.transiogram

Examples

data(ACM)

# Estimate model parameter
x <- multi.tpfit(ACM$MAT5, ACM[, 1:3])

# Set short names for categories 3 and 4
names(x$prop)[3:4] <- c("Clay and Sand", "Gravel and Sand")

# Plot 2-D theoretical sections of
# a multidimensional transiogram
image(x, 40, max.dist=c(20,10,5), which.dire=2:3,
    mar = .7, col=rev(heat.colors(500)),
    breaks=0:500/500, nlevels = 5)