R help - Apr 2013 - Missing data

Dear r-users,

I would like to investigate about how to fill in missing data.  I started with a
complete data and try to introduce missing data into the data series.  Then I
would use some method to fill in the missing data and then compare with the
original data how good it is.  My question is, how do I introduce missing data
in my complete data systematically like for example every 10th data will be
erased and assumed as missing.  Here are some rainfall data:

125
130.3
327.2
252.2
33.8
6.1
5.1
0.5
0.5
0
2.3
0
0
0
0
0
0
0
0
0
0.8
5.1
0
0.3
0
0
0
0
0
0
45.7
43.4
0
0
0
0
0

Thank you so much for any help given.  I hope my question is clear.
	[[alternative HTML version deleted]]

Hello,

Something like this?

x <- scan(text = "
125
130.3
327.2
252.2
33.8
6.1
5.1
0.5
0.5
0
2.3
0
0
0
0
0
0
0
0
0
0.8
5.1
0
0.3
0
0
0
0
0
0
45.7
43.4
0
0
0
0
0
")

putMissing <- function(x, by){
	idx <- by*seq_along(x)
	idx <- idx[which(idx <= length(x))]
	x[idx] <- NA
	x
}

putMissing(x, 10)
putMissing(x, 5)


Hope this helps,

Rui Barradas

Em 25-04-2013 07:41, Roslina Zakaria escreveu:
> Dear r-users,
>
> I would like to investigate about how to fill in missing data.  I started
with a complete data and try to introduce missing data into the data series. 
Then I would use some method to fill in the missing data and then compare with
the original data how good it is.  My question is, how do I introduce missing
data in my complete data systematically like for example every 10th data will be
erased and assumed as missing.  Here are some rainfall data:
>
> 125
> 130.3
> 327.2
> 252.2
> 33.8
> 6.1
> 5.1
> 0.5
> 0.5
> 0
> 2.3
> 0
> 0
> 0
> 0
> 0
> 0
> 0
> 0
> 0
> 0.8
> 5.1
> 0
> 0.3
> 0
> 0
> 0
> 0
> 0
> 0
> 45.7
> 43.4
> 0
> 0
> 0
> 0
> 0
>
> Thank you so much for any help given.  I hope my question is clear.
> 	[[alternative HTML version deleted]]
>
>
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

I read your data into a dataframe
> x <- read.table( "clipboard" )
and renamed the only column
> colnames( x )[1] <- "orig"
With a loop, I created a 2nd column "miss" where in every 10th row the
observation is set to NA:

for( i in 1 : length( x$orig ) )
{
  if( as.integer( rownames( x )[ i ] ) %% 10 == 0 )
  {
    x$miss[i] <- NA
  } else { 
    x$miss[i] <- x$orig[i]
  }
}

This is probably the least elegant of all possible solutions but it works...

Rgds,
Rainer




On Wednesday 24 April 2013 23:41:21 Roslina Zakaria
wrote:
> Dear r-users,
> 
> I would like to investigate about how to fill in missing data.  I started
with a complete data and try to introduce missing data into the data series. 
Then I would use some method to fill in the missing data and then compare with
the original data how good it is.  My question is, how do I introduce missing
data in my complete data systematically like for example every 10th data will be
erased and assumed as missing.  Here are some rainfall data:
> 
> 125
> 130.3
> 327.2
> 252.2
> 33.8
> 6.1
> 5.1
> 0.5
> 0.5
> 0
> 2.3
> 0
> 0
> 0
> 0
> 0
> 0
> 0
> 0
> 0
> 0.8
> 5.1
> 0
> 0.3
> 0
> 0
> 0
> 0
> 0
> 0
> 45.7
> 43.4
> 0
> 0
> 0
> 0
> 0
> 
> Thank you so much for any help given.  I hope my question is clear.
> 	[[alternative HTML version deleted]]
>