I have a question about glm model fitting of my data. The distribution shape is likely to follow a poisson distribution, but the response variable is not count/rate, but continuous decimals with both positive an negative values （as shown below).
There are only a few family types for me to choose in the glm(): binomial(link = "logit") gaussian(link = "identity") Gamma(link = "inverse") inverse.gaussian(link = "1/mu^2") poisson(link = "log") quasi(link = "identity", variance = "constant") quasibinomial(link = "logit") quasipoisson(link = "log")
Could you please give me some suggestions that which one should be more appropriate to my case?
Thanks in advance for your attention and help!