Hi all,
I need to replace missing values in a matrix by 10 % of the lowest available
value in the matrix. I've got a function I've used earlier to replace
negative values by the lowest value, in a data frame, but I'm not sure how
to modify it...
nonNeg = as.data.frame(apply(orig.df, 2, function(col) # Change negative values
to a small value, close to zero
{
min.val = min(col[col > 0])
col[col < 0] = (min.val / 10)
col # Column index
}))
I think this is how to start, but the NA replacement part doesn't work...
newMatrix = as.matrix(apply(oldMatrix, 2, function(col)
{
min.val = min(mData, na.rm = T) # Find the smallest value in the dataset
col[col == NA] = (min.val / 10) # Doesn't work...
col # Column index
}
Does any of you have any suggestions?
Best regards,
Joel
_________________________________________________________________
Hitta kärleken i vinter!
http://dejting.se.msn.com/channel/index.aspx?trackingid=1002952
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Joel F?rstenberg-H?gg wrote:> Hi all, > > > > I need to replace missing values in a matrix by 10 % of the lowest available value in the matrix. I've got a function I've used earlier to replace negative values by the lowest value, in a data frame, but I'm not sure how to modify it... > > > > nonNeg = as.data.frame(apply(orig.df, 2, function(col) # Change negative values to a small value, close to zero > { > min.val = min(col[col > 0]) >> col[col < 0] = (min.val / 10) > col # Column index > })) > > > > I think this is how to start, but the NA replacement part doesn't work... > > > > newMatrix = as.matrix(apply(oldMatrix, 2, function(col) > > { > > min.val = min(mData, na.rm = T) # Find the smallest value in the dataset > > col[col == NA] = (min.val / 10) # Doesn't work... >use is.na(col) t find the NA's. cheers, Paul> col # Column index > > } > > > > Does any of you have any suggestions? > > > > > > Best regards, > > > > Joel > > > > _________________________________________________________________ > Hitta k?rleken i vinter! > http://dejting.se.msn.com/channel/index.aspx?trackingid=1002952 > [[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. >-- Drs. Paul Hiemstra Department of Physical Geography Faculty of Geosciences University of Utrecht Heidelberglaan 2 P.O. Box 80.115 3508 TC Utrecht Phone: +3130 274 3113 Mon-Tue Phone: +3130 253 5773 Wed-Fri http://intamap.geo.uu.nl/~paul
On 01/28/2010 08:35 PM, Joel F?rstenberg-H?gg wrote:> > Hi all, > > > > I need to replace missing values in a matrix by 10 % of the lowest available value in the matrix. I've got a function I've used earlier to replace negative values by the lowest value, in a data frame, but I'm not sure how to modify it... > > > > nonNeg = as.data.frame(apply(orig.df, 2, function(col) # Change negative values to a small value, close to zero > { > min.val = min(col[col> 0]) > > col[col< 0] = (min.val / 10) > col # Column index > })) > > > > I think this is how to start, but the NA replacement part doesn't work... > > > > newMatrix = as.matrix(apply(oldMatrix, 2, function(col) > > { > > min.val = min(mData, na.rm = T) # Find the smallest value in the dataset > > col[col == NA] = (min.val / 10) # Doesn't work... > col # Column index > > } > > > > Does any of you have any suggestions? >Hi Joel, You probably want to use: col[is.na(col)]<-min.val/10 Jim