heading of item response models (IRM). In Econometrics, subjective well-being (SWB) and self-assessed health (SAH) studies …, and in marketing research, Ordered Probit, Ordered Logit, and Interval Regression models are common research platforms. To … single-equation models estimation of the latent linear model by Maximum Likelihood (ML) is routine. But, for higher …

the underlying statistical distributions, a variety of analyticalmethods and simulation-based methods are available. Aside … orhistorical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation have receivedsubstantial … and incremental VaR in either a non-normal analytical setting or a MonteCarlo / historical simulation context.This paper …

Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlomethod for Bayesian analysis of models with ill … the location and scale.Tested on a set of canonical models that feature nearnon-identifiability, strong correlation, and …

implicit statistical arbitrage method. We use a simulation-based Bayesian procedure for predicting stable ratios, defined in a …

Parameter estimates of structural economic models are often difficult to interpret at the light of the underlying … economic theory. Bayesian methods have become increasingly popular as a tool for conducting inference on structural models … properties of the estimator are established for both correctly and incorrectly specified models. A Monte Carlo study reveals the …

We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. We propose a general and … efficient likelihood evaluation method for this class of models via the combination of numerical and Monte Carlo integration … methods. Our methodology explores the idea that only a small part of the likelihood evaluation problem requires simulation. We …

In this paper we use Monte Carlo simulation to investigate the impact of effect size heterogeneity on the results of a …

Highly non-elliptical posterior distributions may occur in several econometric models, in particular, when the … indirect sampling methods in these models, one has to find a good candidate density. In a recent paper - Hoogerheide, Kaashoek … sophisticated neural network simulation techniques is explored. In all examples considered in this paper – a bimodal distribution of …

Likelihood based inference for multi-state latent factor intensity models is hindered by the fact that exact closed … dynamic econometric models. This paper reviews, adapts and compares three different approaches for solving this problem. For …