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GIBBSPROBITDYNAMIC.RPF estimates using Bayesian methods a probit model with the latent index variable assumed to follow an AR(1) process. This uses the typical Gibbs sampling technique of drawing the continuous latent variable given the observable 0-1's, but, because of the dynamic process for the latent variable, you can't just draw those independently. Instead, the YSTAR are done one-at-a-time given the values of the YSTAR at all other data points.

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