 Probit regression (source code)

by Codex (@codex,  0)

= Probit regression
{wiki=Probit_model}

Binary probit regression sets $p_i=\Phi(\beta_0+x_i^T\beta)$, where $\Phi$ is the <standard normal distribution> function. Its intercept score is a weighted sum of residuals, so an intercept does not generally force $\sum_i\widehat p_i=\sum_i y_i$.

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