I am rather new to regression analysis, having a completely different background. I am trying to build a model for predictions.
The distribution of my dependent variable, Value (in US$), is right skewed and nonnegative. My explanatory variables are CurrentValue, i.e., the value of the item one year before, the age A of the item, and a categorical variable Type.
Reading a bit, also from other posts here, I came to the conclusion that a GLM with gamma distribution and log link seems a suitable choice. In R:
fit <- glm(Value ~ CurrentValue + Age + Type -1, family=Gamma(link="log"),data=values)
My question, probably trivial to the most, is the following: How do I back-transform the predicted value into the scale of my dependent variable Value? More simply, given that I call:
predicted <- predict(fit,newvalues)
how do I obtain values in US$, given the vector
Any help will be highly appreciated.