Gold has been recognized as the most important precious metals in the human society. Other than as a medium of exchange, gold has been a consumption and investment product for a long history. It has been recognized a well-positive role in portfolio performance by many financial market practitioners. During the recent financial crisis, gold spot prices have exhibited significant volatility. Thus...

To the Editor:-We read with interest the article by Zhou and Dexter on the use of prediction bounds to assist scheduling of add-on cases.‘ We acknowledge that the authors have addressed an important topic in operating-room efficiency; however, we have certain concerns as to the practical utility of the current version of this approach. Table 1 in their article supplies data on the quality of 50...

In this paper, we study the dual long memory property of the Korean stock market. For this purpose, the ARFIMA–FIGARCH model is applied to two daily Korean stock price indices (KOSPI and KOSDAQ). Our empirical results indicate that long memory dynamics in the returns and volatility can be adequately estimated by the joint ARFIMA–FIGARCH model. We also found that the assumption of a skewed Stude...

We propose two nonlinear Kalman smoothers that rely on Student’s t distributions. The T-Robust smoother finds the maximum a posteriori likelihood (MAP) solution for Gaussian process noise and Student’s t observation noise, and is extremely robust against outliers, outperforming the recently proposed `1-Laplace smoother in extreme situations (e.g. 50% or more outliers). The second estimator, whi...

This paper deals with Dynamic Stochastic General Equilibrium (DSGE) models under a multivariate student-t distribution for the structural shocks. Based on the solution algorithm of Klein (2000) and the gamma-normal representation of the t -distribution, the TaRB-MH algorithm of Chib and Ramamurthy (2010) is used to estimate the model. A technique for estimating the marginal likelihood of the DS...

Inverse probability-weighted marginal structural models with binary exposures are common in epidemiology. Constructing inverse probability weights for a continuous exposure can be complicated by the presence of outliers, and the need to identify a parametric form for the exposure and account for nonconstant exposure variance. We explored the performance of various methods to construct inverse p...

In this paper, we provide two one-factor heavy-tailed copula models for pricing a collateralized debt obligation and credit default index swap tranches: (1) a one-factor double t distribution with fractional degrees of freedom copula model and (2) a one-factor double mixture distribution of t and Gaussian distribution copula model. A tail-fatness parameter is introduced in each model, allowing ...

The t -distribution allows the incorporation of outlier robustness into statistical models while retaining the elegance of likelihood-based inference. In this paper we develop and implement a linear mixed model for the general design of the linear mixed model using the univariate t -distribution. This general design allows a considerably richer class of models to be fit than is possible with ex...

Simple patterns are compelling. When all the observed facts fit into a simple theory or "story," we are intuitively convinced that the pattern must be real rather than random. But how surprising is a simple pattern, really? That is, given a pattern of featural data, such as the properties of a set of objects, how unlikely would the pattern be if they were actually generated at random? In conven...

In this manuscript we present various robust statistical methods popular in the social sciences, and show how to apply them in R using the WRS2 package available on CRAN. We elaborate on robust location measures, and present robust t-test and ANOVA versions for independent and dependent samples, including quantile ANOVA. Furthermore, we present on running interval smoothers as used in robust AN...