spMC (version 0.3.15)

persp.multi_tpfit: Perspective Plots with Multidimensional Transiograms

Description

The function draws perspective-plots the \(2\)-D sections of a predicted multidimensional transiograms computed through ellipsoidal interpolation.

Usage

# S3 method for multi_tpfit
persp(x, mpoints, which.dire, max.dist, main,
      mar, ask = TRUE, col = "white", ...)

Value

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

Arguments

x

an object of the class multi_tpfit, typically with the output of the function multi_tpfit.

mpoints

the number of points per axes. It controls the accuracy of images to plot.

which.dire

a vector with two chosen axial directions. If omitted, all \(2\)-D sections are plotted.

max.dist

a scalar or a vector of maximum length for the chosen axial directions.

main

the main title (on top) whose font and size are fixed.

mar

a scalar or a numerical vector of the form c(bottom, left, top, right) which gives the number of margin lines to be specified on the four sides of image to plot. See par(mar=.).

ask

a logical value; if TRUE, the user is asked for input, before each plot. See par(ask=.).

col

a list of colors which is usually generated by rev(heat.colors()), or with other function for colors.

...

other arguments to pass to the function persp.

Author

Luca Sartore

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, persp.multi_tpfit, persp, pemt, persp.pemt, plot.transiogram

Examples

# \donttest{
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")

# 3D-Plot for a 2-D theoretical sections of
# a multidimensional transiogram
persp(x, 15, max.dist = c(200, 200, 20), which.dire = 2:3,
    mar = .7, col = rainbow(500), theta = 15, phi = 45)
# }