Is it possible to fit a linear model with only a response variable?
Pregunta
If I do this, I get two coefficients (intercept and year)
data <- data.frame(accidents=c(3,1,5,0,2,3,4), year=1:7)
glm(accidents ~ year, family=poisson(link = log), data)
Coefficients:
(Intercept) year
0.7155 0.0557
But the correct answer is 0.944
data <-data.frame(accidents=c(3,1,5,0,2,3,4))
glm(accidents ~ ., family=poisson(link=log), data)
Coefficients:
(Intercept)
0.944
Is there a way to specify the glm formula for just the response variable? If I use the second formula with the first data frame I get the wrong answer because the "." also includes the "year". In the second data frame I'm cheating because there is only one column.
Solución
Here's the incantation that you are looking for:
glm(accidents ~ 1, family=poisson(link = log), data)
Using it with your original data frame:
data <- data.frame(accidents=c(3,1,5,0,2,3,4), year=1:7)
coef(glm(accidents ~ 1, family=poisson(link = log), data))
(Intercept)
0.9444616
Also, as Ben Bolker mentions, the R Introduction document that ships with R includes a nicely informative section on the grammar of the formula interface.
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