Hello,
I am not a regular R user but coming from Python. But I use R for
several special task.
Doing a regression analysis does cost some compute time. But I wonder
when this big time consuming algorithm is executed and if it is done
twice in my sepcial case.
It seems that calling "glm()" or similar does not execute the time
consuming part of the regression code.
It seems it is done when calling "summary(model)".
Am I right so far?
If this is correct I would say that in my case the regression is down
twice with the identical formula and data. Which of course is
inefficient. See this code:
my_function <- function(formula_string, data) {
formula <- as.formula(formula_string)
model <- glm.nb(formula, data = data)
result = cbind(summary(model)$coefficients, confint(model))
result = as.data.frame(result)
string_result = capture.output(summary(model))
return(list(result, string_result))
}
I do call summary() once to get the "$coefficents" and a second time
when capturing its output as a string.
If this really result in computing the regression twice I ask myself if
there is a R-way to make this more efficent?
Best regards,
Christian Buhtz