Dear R friends I´m interested into apply a Jackknife analysis to in order to quantify the uncertainty of my coefficients estimated by the logistic regression. I´m using a glm(family=binomial) because my independent variable is in 0 - 1 format.
My dataset has 76000 obs, and I´m using 7 independent variables plus an offset. The idea involves to split the data in lets say 5 random subsets and then obtaining the 7 estimated parameters by dropping one subset at a time from the dataset. Then I can estimate uncertainty of the parameters. I understand the procedure but I´m unable to do it in R. This is the model that I´m fitting:*glm(f_ocur~altitud+UTM_X+UTM_Y+j_sin+j_cos+temp_res+pp+offset(log(1/off)), data=mydata, family='binomial')* Does anyone have an idea of how can I make this possible? I´d really appreciate if someone could help me with this. Thank you in advance. P.S. More information can be added if needed. Best regards. Lucas. [[alternative HTML version deleted]]
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