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→Latent-variable formulation: : Added another example of error term of the latent variable distribution |
→Latent-variable formulation: Corrected an error ("logit" instead of "log") |
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:<math>\beta_0 = \frac {b_0+a}{2a},\;\; \beta=\frac{\mathbf b}{2a}.</math>
This method is a general device to obtain a conditional probability model of a binary variable: if we assume that the distribution of the error term is Logistic, we obtain the [[logit model]], while if we assume that it is the Normal, we obtain the [[probit model]] and, if we assume that it is the logarithm of a Weibull distrubution, the [[Generalized linear model|complementary log-
== See also ==
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