| 11. | In many cases, there is an unobservable heterogeneity in the probit model.
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| 12. | A probit model including both of these two issues can be represented as:
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| 13. | One such method is the usual probit models.
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| 14. | The normal CDF \ Phi is a popular choice and yields the probit model.
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| 15. | The link function provides the relationship between the linear predictor and the Bayesian probit regression.
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| 16. | In the probit model we assume that it follows a normal distribution with mean zero.
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| 17. | In the case of probit, the link is the cdf of the normal distribution.
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| 18. | This model is then optimized using a customized multinomial probit approach with a Gibbs sampler.
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| 19. | Another model that was developed to offset the disadvantages of the LPM is the probit model.
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| 20. | When nominal variables are to be explained, logistic regression or probit regression is commonly used.
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