R help - Nov 2007 - Calculate aggregate differences

Hi everyone

I am trying to summarize a table with yield estimates of a forest
plantation.  For that I have four blocks and four treatments measured over
a period of 10 years (every year). In each plot trees are measured
(diameters and heights).

With aggregate function I can calculate the average diameter or the total
volume for each plot at any time with something like this:

my_agg <- aggregate(list(Ht = HTO, Dbh = DBH), list(Age = AGE, Block BLOCK,
Treat = TREAT), sum)

my_agg <- aggregate(list(VOL = VOLUME), list(Age = AGE, Block = BLOCK,
Treat = TREAT), sum)

where HTO is the height of the tree
      Ht  average height of trees in each plot at time t
      DBH is the diameter at 1.3 meter height
      Dbh is the average diameter of the plot at time t
      VOL is the [i]th tree volume
      Vol is the volume of the plot at time t

To do actual growth analysis I need to calculate the difference in volume
between t and (t-1) for every block/treatment.

Now the question

How can I use aggregate to calculate the difference of each time series
and have an output like aggregate does?  I know it is imposible to use
diff() within aggregate because it gives me an scalar.
In SAS proc means handles such a thing, and diff() in R is fine for a
single series, but in this case I want to calculate for all the
treatments/blocks at the same time.

I can do the whole using by and some more less elegant procedures, but I
figure there should be a cleaner way as in PROC MEANS.

Any suggestions?

Cristian Montes
NC State University

Hi Cristian,

instead of aggregate, how about something like:


n <- dim(my_agg)[1]
my_agg$vol.diff <- my_agg$Vol - c(NA, my_agg$Vol[1:(n-1)]
my_agg <- my.agg[my.agg$Age > min(my.agg$Age),]


(assumes same minimum age for all treatments)

(not checked)

Cheers,

Andrew

On Thu, Nov 01, 2007 at 12:09:34PM -0400, crmontes at ncsu.edu
wrote:
> Hi everyone
> 
> I am trying to summarize a table with yield estimates of a forest
> plantation.  For that I have four blocks and four treatments measured over
> a period of 10 years (every year). In each plot trees are measured
> (diameters and heights).
> 
> With aggregate function I can calculate the average diameter or the total
> volume for each plot at any time with something like this:
> 
> my_agg <- aggregate(list(Ht = HTO, Dbh = DBH), list(Age = AGE, Block
> BLOCK, Treat = TREAT), sum)
> 
> my_agg <- aggregate(list(VOL = VOLUME), list(Age = AGE, Block = BLOCK,
> Treat = TREAT), sum)
> 
> where HTO is the height of the tree
>       Ht  average height of trees in each plot at time t
>       DBH is the diameter at 1.3 meter height
>       Dbh is the average diameter of the plot at time t
>       VOL is the [i]th tree volume
>       Vol is the volume of the plot at time t
> 
> To do actual growth analysis I need to calculate the difference in volume
> between t and (t-1) for every block/treatment.
> 
> Now the question
> 
> How can I use aggregate to calculate the difference of each time series
> and have an output like aggregate does?  I know it is imposible to use
> diff() within aggregate because it gives me an scalar.
> In SAS proc means handles such a thing, and diff() in R is fine for a
> single series, but in this case I want to calculate for all the
> treatments/blocks at the same time.
> 
> I can do the whole using by and some more less elegant procedures, but I
> figure there should be a cleaner way as in PROC MEANS.
> 
> Any suggestions?
> 
> Cristian Montes
> NC State University
> 
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-- 
Andrew Robinson  
Department of Mathematics and Statistics            Tel: +61-3-8344-9763
University of Melbourne, VIC 3010 Australia         Fax: +61-3-8344-4599
http://www.ms.unimelb.edu.au/~andrewpr
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