The continuous-valued Hopfield neural network (CHN) is a popular and powerful metaheuristic method for combinatorial optimization. However, it is difficult to select appropriate penalty parameters for constraints so as to obtain a feasible and desirable solution by CHN. Thus, various improved...

In this paper, we consider a linear regression model with Gaussian autoregressive errors of order p = 2, which may be nonstationary. Exact inference methods (tests and confidence region) are developed for the autoregressive parameters and the regression coefficients. We generalize the method...

A new algorithm is developed to solve models with heterogeneous agents and aggregate uncertainty that avoids some disadvantages of the prevailing algorithm that strongly relies on simulation techniques and is easier to implement than existing algorithms. A key aspect of the algorithm is a new...

This article investigates the impacts of asymmetric information within a Lucas (1978) asset pricing economy. Asymmetry enters via the assumption that one group of agents is equipped with superior information about the dividend process.(...)

A method of estimating the spectral representation of a generalized bivariate stable distribution is presented, based on a series of maximum likelihood (ML) estimates of the stable parameters of univariate projections of the data. The corresponding stable spectral density is obtained by solving...