= Mixture regression with shared slopes
{title2=$Y_i\mid Z_i=j,x_i\sim N(\alpha_j+x_i^T\beta,\sigma^2)$}
A mixture regression with shared slopes models $Y_i\mid Z_i=j,x_i\sim N(\alpha_j+x_i^T\beta,\sigma^2)$ with common slopes and component-specific intercepts. It jointly estimates mean adjustment and latent groups, rather than fitting a mixture to fixed residuals. If both a global intercept and component offsets are included, an identifying constraint is required. Constant weights assume latent membership proportions do not depend on the covariates.
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