[R] rpart minimum sample size

[Wensui Liu]

amy,
without looking at your actual code, i would suggest you to take a
look at rpart.control()

On 2/27/07, Amy Uhrin <amy.uhrin at noaa.gov> wrote:
> Is there an optimal / minimum sample size for attempting to construct a
> classification tree using /rpart/?
>
> I have 27 seagrass disturbance sites (boat groundings) that have been
> monitored for a number of years.  The monitoring protocol for each site
> is identical.  From the monitoring data, I am able to determine the
> level of recovery that each site has experienced.  Recovery is our
> categorical dependent variable with values of none, low, medium, high
> which are based upon percent seagrass regrowth into the injury over
> time.  I wish to be able to predict the level of recovery of future
> vessel grounding sites based upon a number of categorical / continuous
> predictor variables used here including (but not limited to) such
> parameters as:  sediment grain size, wave exposure, original size
> (volume) of the injury, injury age, injury location.
>
> When I run /rpart/, the data is split into only two terminal nodes based
> solely upon values of the original volume of each injury.  No other
> predictor variables are considered, even though I have included about
> six of them in the model.  When I remove volume from the model the same
> thing happens but with injury area - two terminal nodes are formed based
> upon area values and no other variables appear.  I was hoping that this
> was a programming issue, me being a newbie and all, but I really think
> I've got the code right.  Now I am beginning to wonder if my N is too
> small for this method?
>
> --
> Amy V. Uhrin, Research Ecologist
>
> NOAA, National Ocean Service
> Center for Coastal Fisheries and Habitat Research
> 101 Pivers Island Road
> Beaufort, NC 28516
> (252) 728-8778
> (252) 728-8784 (fax)
> Amy.Uhrin at noaa.gov
>
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-- 
WenSui Liu
A lousy statistician who happens to know a little programming
(http://spaces.msn.com/statcompute/blog)