GRASS program: v.autocorr

[Darrell McCauley]

A new GRASS program to calculate autocorrelation statistics,
v.autocorr, is ready for testing. It is available via anonymous ftp from
	pasture.ecn.purdue.edu:pub/mccauley/v.autocorr.shar.Z
It will probably be put on moon.cecer.army.mil in the very
near future.

I have tested it based upon examples in:
   Daniel A. Griffith, (1987).  Spatial Autocorrelation - A Primer.
   Association of American Geographers.
and it seems to be working fairly well.  It works only for GRASS 
binary vector files labeled with numeric attributes.

****To those who know what spatial autocorrelation is:****
This program calculates a Geary Ratio and Moran Coefficient, standard
errors of each under both randomization and normalization, estimated
population means (Monte Carlo simulation) for both stats under both
assumptions, and Z statistics for testing Ho: spatial
autocorrelation exists.  It also optionally outputs a connectivity
matrix.

Planned enhancements include: 
o  calculation of Wilk-Shapiro statistics at various places in the code
   (e.g., during Monte Carlo simulation, to make sure that I am sampling
   enough to get a good estimate of population means).
o  calculation of population sizes (perhaps someone might need this for
   something)
o  calculation of some measure of sparseness (suggestions?) for the
   connectivity matrix.

****To programmers:****
There's some nifty statistical functions from statlib which I have
ported to K&R C (approx 32 different flavors of random number
generators) included in this code. Deviates can be calculated from
Beta, Chi-square, Exponential, F, Gamma, Multivariate Normal, and many
other distributions.  Documentation for these is included.

--
James Darrell McCauley          Department of Ag Engr, Purdue Univ
mccauley at ecn.purdue.edu         West Lafayette, Indiana 47907-1146
** "Do what is important first, then what is urgent." (unknown) **

P.S. due to time constraints, I regret that I cannot mail to those
     without access to anonymous ftp. Try asking a friend if you
     fit into this category.