memory problem for R

Hello, Yun-Fan: 

      Prof. Ripley's comments will get you started.  Part of the key is 
finding informative ways to subset and summarize the data so you don't 
try to read it all into R at once.  You can read segments using 
arguments "skip" and "nrows" in "read.table".  You can then analyze a 
portion, save a summary, discard the bulk of the data and read another 
portion. 
    
      Beyond this, you may know that Kalman filtering is essentially 
linear regression performed one observation or one group of observations 
at a time, downweighting "older" observations gracefully.  It 
essentially assumes that the regression parameters follow a random walk 
between observations or groups of observations.  I've done ordinary 
least squares with Kalman filtering software one observation at a time, 
just by setting the migration variance to zero.  R software for Kalman 
filtering was discussed recently in this list;  to find it, I would use 
the search facilities described in the posting guide at the end of every 
r-help email. 

      hope this helps. 
      spencer graves

memory problem for R

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