The smoothing distribution of dynamic probit models with Gaussian state
...
Binary regression models represent a popular model-based approach for bi...
Bayesian binary regression is a prosperous area of research due to the
c...
A broad class of models that routinely appear in several fields can be
e...
Multinomial probit (mnp) models are fundamental and widely-applied regre...
Recently, Fasano, Rebaudo, Durante and Petrone (2019) provided closed-fo...
Multinomial probit models are widely-implemented representations which a...
State-of-the-art methods for Bayesian inference on regression models wit...
State-of-the-art methods for Bayesian inference on regression models wit...
Non-Gaussian state-space models arise routinely in several applications....