Boosting algorithms for fitting generalized linear, additive and interaction models to potentially high-dimensional data. The current relase version can be found on CRAN (http://cran.r-project.org/package=mboost).
I have recently been working with mboost, especially gamboost, for the first time. For a deeper understanding of how the algorithm works, I calculated the first iterations of a basic example manually using categorical data and only a single linear base learner. There were some differences between the coefficients I calculated and the ones mboost provides. It seems like mboost provides the „bare“ coefficients and replaces the base level coefficient with zero. I was expecting all coefficients to be corrected in perspective to the base level. Here is short example:
`library(mboost)
x<-as.factor(mtcars$carb)
y<-mtcars$mpg*10
GAM<-gamboost(y~bols(x, intercept = FALSE), family = Poisson())
I have recently been working with mboost, especially gamboost, for the first time. For a deeper understanding of how the algorithm works, I calculated the first iterations of a basic example manually using categorical data and only a single linear base learner. There were some differences between the coefficients I calculated and the ones mboost provides. It seems like mboost provides the „bare“ coefficients and replaces the base level coefficient with zero. I was expecting all coefficients to be corrected in perspective to the base level. Here is short example:
`library(mboost)
x<-as.factor(mtcars$carb) y<-mtcars$mpg*10
GAM<-gamboost(y~bols(x, intercept = FALSE), family = Poisson())
coef(GAM[1])
nu<-0.1 OffsetWert<-log(mean(y), base = exp(1)) negGradient<-y-exp(OffsetWert) mtcars_neu<-data.frame(mtcars, negGradient) Koef_mtcars<-aggregate(mtcars_neu$negGradient, list(mtcars_neu$carb), mean)
The coefficients mboost provides seem to be the following:
Koef_mtcars$x*nu
I was expecting the standardized coefficients to be as follow:
I use subtraction instead of division because we're using a loglink function
Umnormierte_Koef<-(Koef_mtcars$x-Koef_mtcars$x[1])*nu Umnormierte_Koef`
I would be happy about any help or hints to solve the problem!