simulate model parameters from the Partially Censored Posterior, and PCP-QERMit, an Importance Sampling method that is …

of the posterior distribution of the parameters of interest given the data. This may be permissible when the sample size … samples. We then study the finite-sample performance of the proposed estimators by a Monte Carlo experiment with design …

In a binary logit analysis with unequal sample frequencies of the twooutcomes the less frequent outcome always has … probabilities is mostacute. It affects two common diagnostics, the within-sample 'percentagecorrectly predicted' and the …

This paper reports simulation experiments, applying the cross entropy method suchas the importance sampling algorithm … indicate a considerable improvement ofthe performance of the importance sampling estimators, where performance is mea-sured by … the relative error of the estimate, by the relative error of the estimator,and by the gain of the importance sampling …

high-frequency variables are transformed by means of a mixed-data sampling weighting scheme. The resulting dynamic model … of timely information from high-frequency variables. We aim to verify in-sample and out-of-sample performances of the … findings are promising. Our proposed score-driven dynamic model with mixed-data sampling weighting outperforms competing models …

risk. The key insight behind our importance sampling based approach is the sequential construction of marginal and …

average' and do not provide conditions under which such optimality prevails. We show in a finite sample setting that score …