Estimating VAR models for the term structure of interest rates

In this paper we follow the work of Evans and Marshall and propose new approaches for modelling the joint development of macro variables and the returns of government bond yields of several maturities. The models are estimated and compared with other forecasting schemes previously proposed in the literature, especially those relying on univariate, VAR and error correction methods. The models are then used to judge the hypothesis that the information content of macro variables and the term structure of interest rates as a whole help improving forecasting performance. Our main conclusion is quite simple: if one is interested in computing short-term forecasts, then there is no significant improvement in incorporating information other than the one already present in past observations of the yield at hand; however, if one worries about long-term forecasts (which is frequently the case with pension insurance companies), then the information content of macro variables and the term structure can improve forecasting performance.     

指数分布危险函数的经验Bayes双侧检验的收敛速度: Ⅱ型截尾情形

本文讨论了Ⅱ型截尾情形下指数分布危险函数的经验Bayes (EB)双侧检验问题. 利用概率密度函数的核估计构造了经验Bayes检验函数, 在适当的条件下获得了它的收敛速度.     

Analysis of an MMPP/G/1/K queue with queue length dependent arrival rates,and its application to preventive congestion control in telecommunication networks

Recently telecommunication networks have been designed in order to transfer all types of information services such as voice, data and video. Next generation wireless networks has been developed to integrate the existing technologies and to support comprehensive services. As the traffics of diverse services have properties of timecorrelation and burstiness, unpredictable statistical fluctuation of traffic streams may cause congestion. To suggest a congestion control scheme which controls arrival rates according to the queue length, we consider an MMPP/G/1/K queue with queue length dependent arrival rates. The effect of system parameters on performance measures also is explained with the numerical examples.     

Continuous-Time Approximation of Short-Term Interest Rates in Generalized Ho-Lee Framework

In this paper, we study the weak convergence of short-term interest rate processes in multinomial (one-factor) and squared binomial (two-factor) generalizations of the Ho-Lee framework. We show that, under appropriate conditions on the rate of convergence of state probabilities and volatility parameter, in the one-factor case, the spot interest rate process converges to either Wiener process or superposition of Poisson processes. In the two-factor case, the limit process can have the form of the superposition of Wiener and Poisson components. The asymptotic results are proved under risk-neutral probability and local alternatives. Research is supported by the Lithuanian State Science and Studies Foundation, program “Mathematical Models of Lithuanian Economy for Forecasting of the Macroeconomic Processes” (registration No C-03004). __________ Translated from Lietuvos Matematikos Rinkinys, Vol. 45, No. 3, pp. 287–314, July–September, 2005.     

Efficient computation of time-based customer service levels in a multi-item, multi-echelon supply chain: A practical approach for inventory optimization

Time-based item fill rates, or “channel” fill rates, are the building blocks needed to evaluate steady-state compliance with time-based customer service agreements. Exact computation of channel fill rates is both difficult and time-consuming, yet their accurate assessment is essential for system-wide inventory optimization. We describe and validate a practical method for computing channel fill rates in a multi-item, multi-echelon service parts distribution system. A simulation study is presented which shows that, in a three-echelon setting, our estimation errors are very small over a wide range of base stock level vectors. A more accurate, though less efficient, approximation method is also evaluated for comparison.     

Probabilistic inference of reaction rate parameters from summary statistics

This investigation tackles the probabilistic parameter estimation problem involving the Arrhenius parameters for the rate coefficient of the chain branching reaction H + O₂ → OH + O. This is achieved in a Bayesian inference framework that uses indirect data from the literature in the form of summary statistics by approximating the maximum entropy solution with the aid of approximate bayesian computation. The summary statistics include nominal values and uncertainty factors of the rate coefficient, obtained from shock-tube experiments performed at various initial temperatures. The Bayesian framework allows for the incorporation of uncertainty in the rate coefficient of a secondary reaction, namely OH + H₂ → H₂O + H, resulting in a consistent joint probability density on Arrhenius parameters for the two rate coefficients. It also allows for uncertainty quantification in numerical ignition predictions while conforming with the published summary statistics. The method relies on probabilistic reconstruction of the unreported data, OH concentration profiles from shock-tube experiments, along with the unknown Arrhenius parameters. The data inference is performed using a Markov chain Monte Carlo sampling procedure that relies on an efficient adaptive quadrature in estimating relevant integrals needed for data likelihood evaluations. For further efficiency gains, local Padé–Legendre approximants are used as surrogates for the time histories of OH concentration, alleviating the need for 0-D auto-ignition simulations. The reconstructed realisations of the missing data are used to provide a consensus joint posterior probability density on the unknown Arrhenius parameters via probabilistic pooling. Uncertainty quantification analysis is performed for stoichiometric hydrogen–air auto-ignition computations to explore the impact of uncertain parameter correlations on a range of quantities of interest.     

Temperature analysis of one-dimensional NiTi shape memory alloys under different loading rates and boundary conditions

Superelastic polycrystalline NiTi shape memory alloys under tensile loading accompany the strain localization and propagation phenomena. Experiments showed that the number of moving phase fronts and the mechanical behavior are very sensitive to the loading rate due to the release/absorption of latent heat and the material’s inherent temperature sensitivity of the transformation stress. In this paper, the moving heat source method based on the heat diffusion equation is used to study the temperature evolution of one-dimensional superelastic NiTi specimen under different loading rates and boundary conditions with moving heat sources or a uniform heat source. Comparisons of temperature variations with different boundary conditions show that the heat exchange at the boundaries plays a major role in the nonuniform temperature profile that directly relates to the localized deformation. Analytical relation between the front temperature of a single phase front, the inherent Clausius–Clapeyron relation (sensitivity of the material’s transformation stress with temperature), heat transfer boundary conditions and the loading rate is established to analyze the nucleation of new phase fronts. Finally, the rate-dependent stress hysteresis is also simply discussed by using the results of temperature analyses.     

复合材料层合梁在横向线载荷下的脱层扩展

基于可动边界变分原理对层合梁脱层扩展进行了分析;考虑了脱层间的接触效应,建立了层合梁在横向线载荷作用下的非线性控制微分方程及相应的定解条件;应用Griffith准则导出了脱层前缘各点处的能量释放率表达式;通过算例讨论了脱层长度、脱层深度、几何尺寸、材料性质等因素对脱层扩展的影响.研究表明:脱层越长、越深、横向载荷越大,脱层越容易扩展;梁的长高比L/h及材料的E_(11)/E_(22)越大,脱层越不易发生扩展.     

高真空多层绝热结构中一氧化钯吸氢特性研究

对高真空下的一氧化钯吸附氢气的特性进行了分析和研究,实验测定了一氧化钯吸附氢气的机理,不同条件下一氧化钯对氢气的吸附特性,以及设置一氧化钯对夹层漏放气的影响。实验证明,在夹层中使用恰当的混合吸附剂,可以有效减小夹层的漏放气量,提高低温储罐的寿命。