text: """
  StructLMM
  =========
  
  Let n be the number of samples.
  StructLMM [1] extends the conventional linear mixed model by including an
  additional per-individual effect term that accounts for genotype-environment
  interaction, which can be represented as an n×1 vector, 𝛃.
  The model is given by
  
      𝐲 = 𝙼𝛂 + 𝐠𝛽 + 𝐠⊙𝛃 + 𝐞 + 𝛆,
  
  where
  
      𝛽 ∼ 𝓝(0, 𝓋₀⋅ρ), 𝛃 ∼ 𝓝(𝟎, 𝓋₀(1-ρ)𝙴𝙴ᵀ), 𝐞 ∼ 𝓝(𝟎, 𝓋₁𝚆𝚆ᵀ), and 𝛆 ∼ 𝓝(𝟎, 𝓋₂𝙸).
  
  The vector 𝐲 is the outcome, matrix 𝙼 contains the covariates, and vector 𝐠 is the
  genetic variant.
  The matrices 𝙴 and 𝚆 are generally the same, and represent the environment
  configuration for each sample.
  The parameters 𝓋₀, 𝓋₁, and 𝓋₂ are the overall variances.
  The parameter ρ ∈ [𝟶, 𝟷] dictates the relevance of genotype-environment interaction
  versus the genotype effect alone.
  The term 𝐞 accounts for additive environment-only effects while 𝛆 accounts for
  noise effects.
  
  .. [1] Moore, R., Casale, F. P., Bonder, M. J., Horta, D., Franke, L., Barroso, I., &
     Stegle, O. (2018). A linear mixed-model approach to study multivariate
     gene–environment interactions (p. 1). Nature Publishing Group.
  """
  from ._lmm import StructLMM
  from ._testit import test
  
  __version__ = "0.3.2"
  
  __all__ = ["StructLMM", "__version__", "test"]
  