In statistics, a **probit model** is a type of regression where the dependent variable can only take two values, for example married or not married. The name is from * probability* +

*un*.

**it**A probit model is a popular specification for an ordinal or a binary response model that employs a probit link function. This model is most often estimated using standard maximum likelihood procedure, such an estimation being called a **probit regression**.

Probit models were introduced by Chester Bliss in 1934, and a fast method for computing maximum likelihood estimates for them was proposed by Ronald Fisher in an appendix to Bliss 1935.

Read more about Probit Model: Introduction, Maximum Likelihood Estimation, Berkson's Minimum Chi-square Method, Gibbs Sampling

### Other articles related to "probit model, model, models, probit":

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**Probit Model**- Gibbs Sampling

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**model**can be described as From this, we can determine the full conditional densities needed The result for β is given in the article on Bayesian linear ... using approximations to the normal CDF and the

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... In the Ordinary

**Probit model**, one latent variable is used, in the bivariate

**probit model**there are two and ... variables are defined as Fitting the bivariate

**probit model**involves estimating the values of ... To do so, the Likelihood of the

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... In statistics and econometrics, the multinomial

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**probit model**used to estimate several ... budget are correlated (both decisions are binary), then the multinomial

**probit model**would be appropriate ...

### Famous quotes containing the word model:

“One of the most important things we adults can do for young children is to *model* the kind of person we would like them to be.”

—Carol B. Hillman (20th century)