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.
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