following (considering your example):

1) let knn = sqrt(30) = 5 or 6 (you may define any other value)

2) Visit the 30 locations along a random path

3) At location i, consider the nearest 6 points. Calculate a re-sampling

probability of each of these 6 points such that the closer the point to

point i, the higher the probability. (use the inverse distance and

normalize, or use Kernel function)

4) Re-sample point i according the probabilities caclulated above

5) proceed along the random path to re-sample all points and obtain 1

realization.

6) repeat many times with different random paths (10000....).

7) Calculate the fraction of F, and S (if you are working with growth

height, you can categorize it) from the obtained realizations.

Good luck..

A. Ali

_________________________________________________________

A. Ali, Ph.D., P.E.

New Mexico State Engineer Office

P.O.Box 25102, Santa Fe, NM 87504

e-mails: aali@...; or aali@...

Web: http://www.engineering.usu.edu/Departments/cee/Faculty/ulall/

Phone: 505-827-6125 Fax: 505-827-6188

_________________________________________________________

> I am looking for a test that planting location

and

> influences seedling growth. For example,

> 30 seedlings are planted in a uniform medium.

> The S represent "slow growers" and the F

> represent "fast growers".

>

> F S S F S F

> F F S F S S

> S S F S F S

> S S S F S F

> F S F S F S

>

> The above is a simplified example as

> I have height growth for each seedling

> and about 600 seedlings.

>

> One approach would be a jacknife or bootstrap

> type approach of randomly assigning each seedling

> growth to each location and repeating the randomiztion

> trials 1,000 times. Then compare the original distribution

> with the 1,000 randomization trial distributions. But

> how?

>

> The null hypothesis is that the site is uniform and

> all variablity of seedling growth is due to factors

> other than seedling location.

>

> Any suggestions would be appreciated. I will post

> a summary on April 15, 1997.

>

> Thank you.

>

> Dave Verbyla

> Associate Professor of GIS/Remote Sensing

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