CARsimu: Conditional AutoRegressive surface simulator

In hdeco: Hierarchical DECOmposition of Entropy for Categorical Map Comparisons

Description

A stationary tool for simulating a surface (as a matrix of values) with specified spatial autocorrelation parameters. The simulation return 2^level*2^level real-valued surface (e.g., landscape) based on the FFT algorithm and the spectral (or autocorrelation theorem using first and second order neighbours in N-S, E-W, NW-SE, and NE-SW directions.

Usage

CARsimu(level = 5, row1 = 0.2499999, row2 = 0, col1 = 0.2499999, col2 = 0, rc1 = 0, cr1 = 0)

Arguments

level	Integer: controls the dimensions of the output surface (2^level*2^level)
row1	First order neighbour East-West autocorrleation parameter
row2	Second order neighbour East-West autocorrelation parameter
col1	First order neighbour North-South autocorrelation parameter
col2	Second order neighbour North-South autocorrelation parameter
rc1	First order neighbour NW-SE autocorrelation parameter
cr1	First order neighbour NE-SW autocorrelation parameter

Details

The sum of all six autocorrelation parameters MUST be less than 0.5. Their effect is highly non-linear, thus there is a marked difference beetween 0.499 and 0.499999. This implementation corresponds to the homogeneous (stationary) conditional autoregressive (CAR) model.

Value

Returns a 2^level*2^level matrix of real numbers. It is possible to use the image() or imaks() functions to graphically display the surface. Saving the output from this function into a new object is likely the most desireable usage. Ths surface can then be factored to produce binary maps with specified proportions as in Remmel and Csillag (2003).

Note

This function was originally called ujabki() - some earlier versions may be available elsewhere under this name.

Author(s)

Sandor Kabos, Ferenc (Ferko) Csillag, and Tarmo Remmel

References

Remmel, T.K. and F. Csillag. 2003. When are two landscape pattern indices significantly different? Journal of Geographical Systems 5(4):331-351.

Examples

carimage <- CARsimu(level=5, row1=0.2499999, row2=0, col1=0.2499999, col2=0, rc1=0, cr1=0)
image(carimage)

hdeco documentation built on May 30, 2017, 8:26 a.m.