Empirical convergence analyses have helped provide insight as to whether economies are converging. Previous works on convergence have tended to focus on a particular economic indicator exclusively, even though the convergence process has multiple components. Improved estimates of convergence are...

This paper describes a GAUSS program of a Markov-chain sampling algorithm for GARCH models proposed by Nakatsuma (1998). This algorithm allows us to generate Monte Carlo samples of parameters in a GARCH model from their joint posterior distribution. The samples obtained by this algorithm are...

Probabilistic programming allows artificial systems to better operate with uncertainty, and stochastic arithmetic provides a way to carry out approximate computations with few resources. As such, both are plausible models for natural cognition. The authors' work on the automatic design of...

Abstract Individual-level models (ILMs) are a class of complex, statistical models that are often fitted within a Bayesian framework, and which can be suitable for modeling infectious disease spread. The deviance information criterion (DIC) is a model comparison tool that is appropriate for...

Abstract Marginal structural models (MSM) with inverse probability weighting (IPW) are used to estimate causal effects of time-varying treatments, but can result in erratic finite-sample performance when there is low overlap in covariate distributions across different treatment patterns....

Abstract This paper presents statistical inference procedures from S pn , a process capability index for asymmetrical processes proposed by Boyles. From the frequentist perspective, a conservative lower confidence bound is given. From the Bayesian perspective, the SIR algorithm is used to obtain...

Purpose – The purpose of this paper is to examine the relevance of accounting variables to explain the evolution of a company's share price; and more specifically, we analyse the influence of cash flow and book value on the evolution of the share price, taking into account certain covariates...

Purpose The growing availability of naturalistic driving datasets (NDDs) presents a valuable opportunity to develop various models for autonomous driving. However, while current NDDs include data on vehicles with and without intended driving behavior changes, they do not explicitly demonstrate a...