spMC (version 0.3.2)

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, pemt, image.pemt, 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(200,200,20), which.dire=2:3,
    mar = .7, col=rev(heat.colors(500)),
    breaks=0:500/500, nlevels = 5)