example-neutrino

Spey plugin for the likelihood presented in arXiv:2007.08526 where the likelihood has been implemented in the following form:

$$ \mathcal{L}(\mu, \theta) = \left[\prod_{i\in{\rm channels}}\prod_{j_i\in {\rm bins}} {\rm Poiss}(n^j|(\mu n_s^j + n_b^j)(1 + \theta^j\sigma_b^j))\right] \cdot \prod_{k\in{\rm nuis}}\mathcal{N}(\theta^k | 0, 1) $$

Here $n$ stands for the data, $n_s$ and $n_b$ are the signal and background yields, $\sigma_b$ are the background uncertainties. $\mu$ is the parameter of interest and $\theta$ are the nuisance parameters.

This plug-in can be installed from GitHub with pip

python -m pip install --upgrade "git+https://github.com/SpeysideHEP/example-neutrino"

or from the locally cloned repository

python -m pip install --upgrade .

command and can be used with spey.get_backend("example.neutrino") function.

import numpy as np
import spey

pdf_wrapper = spey.get_backend("example.neutrino")
stat_model = pdf_wrapper(
    signal_yields=np.array([12, 15]),
    background_yields=np.array([50.0, 48.0]),
    data=np.array([38, 47]),
    absolute_uncertainties=np.array([11, 25]),
)
stat_model.likelihood()
# 7.42425771274118