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Everything about GHK algorithm
Importance sampling method
The GHK algorithm is an importance sampling method for simulating choice probabilities in the multivariate probit model. These simulated probabilities can be used to recover parameter estimates from the maximized likelihood equation using any one of the usual well known maximization methods. Train has well documented steps for implementing this algorithm for a multinomial probit model. What follows here will apply to the binary multivariate probit model. Wikipedia ā
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- Read the overview: GHK algorithmA 5-minute orientation
- Read the landmark paper: Transitive Closure Algorithm using Binary OR Operation: Primes Algorithm, GHK AlgorithmCited 0 times
- Go sideways: Multivariate normal distributionA closely related topic
- Go sideways: Folded normal distributionA closely related topic
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