mixplot {spMC} | R Documentation |
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, ...)
Arguments
x |
a |
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 |
... |
other arguments to pass to the function |
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.
Value
An image is produced on the current graphics device. No values are returned.
Author(s)
Luca Sartore drwolf85@gmail.com
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
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))