[R] Imputing missing values in time series

[Erik Iverson]

I think my example should work for you, but I couldn't think of a way to 
do this without an interative while loop.

test <- c(1,2,3,NA,4,NA,NA,5,NA,6,7,NA)

while(any(is.na(test)))
test[is.na(test)] <- test[which(is.na(test))-1]

  test
  [1] 1 2 3 3 4 4 4 5 5 6 7 7

Horace Tso wrote:
> Folks,
> 
> This must be a rather common problem with real life time series data
> but I don't see anything in the archive about how to deal with it. I
> have a time series of natural gas prices by flow date. Since gas is not
> traded on weekends and holidays, I have a lot of missing values,
> 
> FDate	Price
> 11/1/2006	6.28
> 11/2/2006	6.58
> 11/3/2006	6.586
> 11/4/2006	6.716
> 11/5/2006	NA
> 11/6/2006	NA
> 11/7/2006	6.262
> 11/8/2006	6.27
> 11/9/2006	6.696
> 11/10/2006	6.729
> 11/11/2006	6.487
> 11/12/2006	NA
> 11/13/2006	NA
> 11/14/2006	6.725
> 11/15/2006	6.844
> 11/16/2006	6.907
>  
> What I would like to do is to fill the NAs with the price from the
> previous date * gas used during holidays is purchased from the week
> before. Though real simple, I wonder if there is a function to perform
> this task. Some of the imputation functions I'm aware of (eg. impute,
> transcan in Hmisc) seem to deal with completely different problems. 
> 
> 2.5.0/Windows XP
> 
> Thanks in advance.
> 
> HT
> 
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