spMC (version 0.3.15)

mixplot: Plot of Multiple One-dimensional Transiograms

Description

The function makes a graphical representation of transition probabilities by the use of multiple transiograms.

Usage

mixplot(x, main, legend = TRUE, ...)

Value

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

Arguments

x

a list object whose elements are of the class transiogram (typically with the output of the function transiogram or predict.tpfit).

main

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

legend

a logical value for printing the legend in the graphic. It is TRUE by default.

...

other arguments to pass to the function plot.

Author

Luca Sartore

Details

Transiogram is a diagram which is drawn for a single pair of categories in the direction \(\phi\). It shows the transition probabilities in the \(y\)-axis for some specific lags in the \(x\)-axis.

This function permits a graphical approach to compare theoretical vs. empirical transition probabilities for multiple directions.

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.

Li, W. (2007) Transiograms for Characterizing Spatial Variability of Soil Classes. Soil Science Society of America Journal, 71(3), 881-893.

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

See Also

transiogram, tpfit, predict.tpfit, plot.transiogram, image.multi_tpfit, plot

Examples

# \donttest{
data(ACM)

# Estimate empirical transition 
# probabilities by points
ETr <- transiogram(ACM$MAT3, ACM[, 1:3], c(0, 0, 1), 100)

# Estimate the transition rate matrix
RTm <- tpfit(ACM$MAT3, ACM[, 1:3], c(0, 0, 1))

# Compute transition probabilities 
# from the one-dimensional MC model
TPr <- predict(RTm, lags = ETr$lags)

# Plot empirical vs. theoretical transition probabilities
mixplot(list(ETr, TPr), type = c("p", "l"), pch = "+", col = c(3, 1))
# }