See ?na.exclude
On Fri, 23 Jan 2009, Neil Beddoe wrote:
Hi.
I need to apply run a regression analysis for groups of data of fixed
length:100 As, 100 Bs, 100 Cs etc.
eg
x
Key Value
A 1
A 21.2
A 4
A 6.5
...repeat 96 times with differing values of A
B 1
B 2.3
B NA
B 6.5
...repeat 96 times with differing values of B
etc
I run these against a linear model using tapply(data$Value,
data$Key,FUN=regr,100) where
regr<-function(x,w)
{
#run the model against the last w values of x
lm((x[length(x)-w):length(x)]~myModel(w))
}
In the results, I want to return NA for any Key group where one or more of the
values is NA. If I run the above I get a regression structure ignoring the
missing values and returning values for data that contains NA. Using
na.action=na.fail or na.action=NULL causes the whole tapply function to fail
and I get nothing. Is there a way I can get lm to return NA if any of the
values in the data are NA but valid numbers for complete data?
I realise that I could remove the groups with NAs but I'm running the
regressions over multiple time periods and most of the data groups will have a
full complement of data for at least some of these periods. It becomes a pain
to manage NAs if I do that.
Sorry if the above is a little unclear.
Thanks
Neil
--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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