R help - Feb 2009 - Log transformation and -Inf values for use in glm()

Hello,
   I am writing regarding log transformation of data in a single  
matrix column, and subsequent use of these data in a glm model fit. I  
have a data matrix in which I am using the log function to transform  
the values. This transformation results in -Inf values in some places,  
though. I then receive an error when this matrix is used in the glm  
function, and would like to know this can be avoided.
   I have attempted several methods already including the use of  
na.exclue commands in the glm statement:
> DistributionT<-glm(EarlyLn$yoyras~EarlyLn$temp,family=gaussian(link  
> = "identity"),na.exclude)
I have also attempted to use the is.finite command:

EarlyLn$yoyras<-EarlyLn[is.finite(EarlyLn$yoyras)==T,]

I know another option would be to use a type of find and replace  
command to remove entire rows of the matrix that contain 0's (before  
log transformation) or -Inf (after transformation), but I do not know  
how this is done.

Thank you for any advice or tips regarding conducting this  
transformation and feeding the data matrix into glm.

Sincerely,
Paul S.

Paul,

On Fri, Feb 6, 2009 at 3:25 PM, Paul Warren Simonin
<Paul.Simonin at uvm.edu> wrote:
> Hello,
>  I am writing regarding log transformation of data in a single matrix
> column, and subsequent use of these data in a glm model fit. I have a data
> matrix in which I am using the log function to transform the values. This
> transformation results in -Inf values in some places, though. I then
receive
> an error when this matrix is used in the glm function, and would like to
> know this can be avoided.
>  I have attempted several methods already including the use of na.exclue
> commands in the glm statement:
>
>> DistributionT<-glm(EarlyLn$yoyras~EarlyLn$temp,family=gaussian(link
>> "identity"),na.exclude)
>
> I have also attempted to use the is.finite command:
>
> EarlyLn$yoyras<-EarlyLn[is.finite(EarlyLn$yoyras)==T,]
>
> I know another option would be to use a type of find and replace command to
> remove entire rows of the matrix that contain 0's (before log
> transformation) or -Inf (after transformation), but I do not know how this
> is done.
>
> Thank you for any advice or tips regarding conducting this transformation
> and feeding the data matrix into glm.
>
> Sincerely,
> Paul S.
In general, use syntax like this:

glm(yoyras ~ log(temp), data = EarlyLn, subset = temp > 0)

However, it's bad statistical practice to use a transformation that
causes you to lose data. One approach is to add a constant to temp
via:

glm(yoyras ~ log(temp + 1), data = EarlyLn, subset = temp > 0)

with the disadvantage being that the constant you choose is arbitrary
but affects your inferences.

Stephen
Rochester, MN USA