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Sometimes, a more complex but more accurate model is needed when the standard off-the-shelf models just do not cut it. That is the message from researchers from KAUST’s Statistics Program. One ...

Analyses of multivariate ordinal probit models typically use data augmentation to link the observed (discrete) data to latent (continuous) data via a censoring mechanism defined by a collection of ...

Joint estimation of farmers' farm and off-farm work participation requires a multivariate probit model, in which the number of equations is twice the number of household members. Where there are more ...

Multivariate binary data arise in a variety of settings. In this paper, we propose a practical and efficient computational framework for maximum likelihood estimation of multivariate probit regression ...