I'm trying to do Dirichlet Regression using Python. Unfortunately I cannot find a Python package that does the job. So I tried to call R library DirichletReg using rpy2. However, it is not very intuitive to me how to call a regression function such as DirichReg(Y ~ X1 + X2 + X3, data=predictorData) where Y = DR_data(compositionalData). I saw an example of calling linear regression function lm in the documentation of rpy2. But my case is slightly different as Y is not a column name in the table but an R object DR_data.
I'm wondering what the proper way is to do this, or whether there is a Python package for Dirichlet Regression.
You can send objects into the "Formula" environment from python. This example is from the rpy2 docs:
import array
from rpy2.robjects import IntVector, Formula
from rpy2.robjects.packages import importr
stats = importr('stats')
x = IntVector(range(1, 11))
y = x.ro + stats.rnorm(10, sd=0.2)
fmla = Formula('y ~ x')
env = fmla.environment
env['x'] = x
env['y'] = y
fit = stats.lm(fmla)
You can also create named variables in the R environment (outside the Formula). See here. Worst case scenario, you move some your python data into R through rpy2, then issue the commands directly in R through the rpy2 bridge as described here.