R help - Aug 2008 - (no subject)

Hi, I am working with R and I have some doubts. I working with daily data of
MNEE parameter for 6 years (2001:2006). What I am trying to do is to replace
missing data for a particular period of time of a particular year, with the mean
of that variable for the rest of the years during that given period.For instance
if I have missing data during the period 100:1000 during the year 2002 I want to
replace that gap with the mean of the other five years. Apparently it is working
but after running it gives an error:  Error in if (trim > 0 && n >
0) { : missing value where TRUE/FALSE neededWhat does it mean? Because after
doing the means there is not NA values. I attach the code I wrote. If you need
any explanation about the variables, please tell me.
 
All my best
 
Laura
 
  
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Hi


r-help-bounces at r-project.org napsal dne 14.08.2008 16:34:32:
> 
> Hi, I am working with R and I have some doubts. I working with daily 
data of 
> MNEE parameter for 6 years (2001:2006). What I am trying to do is to 
replace 
> missing data for a particular period of time of a particular year, with 
the 
> mean of that variable for the rest of the years during that given 
period.For 
> instance if I have missing data during the period 100:1000 during the 
year 
> 2002 I want to replace that gap with the mean of the other five years. 
> Apparently it is working but after running it gives an error:  Error in 
if 
> (trim > 0 && n > 0) { : missing value where TRUE/FALSE
neededWhat does
it 
> mean? Because after doing the means there is not NA values. I attach the 
code 
> I wrote. If you need any explanation about the variables, please tell 
me.

try

debug(name.of.your.function)

and see what it is actually doing. My guess is that using na.rm = FALSE in 
mean computation does not compute mean but results in NA. 

Based on your description I would use other approach.
Preparing faked data

period <- rep(1:5,10)
year <- rep(2001:2010, each=5)
daf <- data.frame(year, period, value=rnorm(50))
daf$value[c(10,17,25)] <- NA

repl <- tapply(daf$value, daf$period, mean, na.rm=T)
# computing mean for each period in all years
not <- which(is.na(daf$value))
# estimating which values are necessary to replace

daf$value[not] <- repl[daf$period[not]]
# replacing those values with corresponding means

Is this what you want?

Regards
Petr

> 
> All my best
> 
> Laura
> 
> 
> _________________________________________________________________
> 
> 
> [p??loha period1.txt odstran?na u?ivatelem Petr PIKAL/CTCAP] 
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