Hello,
It's not easy to express clearly what I have in mind by stochastic growth
models. I've
been working with a couple of titles -Stochastic Models in
Biology, for one, but both date back a decade or more.
I'll try to illustrate the model a little more.
A reasonably comparable situation is Bolker's analysis of
how many flowers are created on a given plant among a patch
of plants, then comparing patches of plants at different
locations. Then, I believe it's possible to determine the
degree to which number of flowers appears to be dependent on
other variables, like plant height, or root depth.
Finally, I would like to add to these analyses, one which,
having determined a stochastically(if I'm using this word
correctly) distributed parameter for the average number of flowers on a plant
from patch 1 as opposed to a plant from patch 2 (patch 1(N(mu, sigma)), patch
2(N(mu,
sigma)),...) would constitute a growth model for each patch
over time, I think maybe something like:
df(patch 1) =r1*f0+ exp^(r1*t)
dt
df(patch 2) =r2*f0+ exp^(r2*t)
dt
It would be nice to be able to add the other effects here:
plant height, and others, as further parameters in each
equation.
I think it's likely these models have been done in biology,
though I don't seem to find exactly how to do it in Bolker's
book, and as a non-biologist, I 'm not sure where to look to
find it. Maybe one can see that I'd like to be able to
transfer this kind of model to use with other kinds of data
from other fields!
Again, I hope that some significant predictors like height and root length would
help define a plant's likely number of flowers. There's a good basic
outline of the model I'm trying to make( it is about bears populations
changing over time):
www.fish.washington.edu/.../Stochastic%20Population%20Models.ppt
It's just that it seems someone else may have started a path in this
direction in connection with R or another software, ...
-s
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