Forecast robustness in macroeconometric models

This paper investigates potential invariance of mean forecast errors to structural breaks in the data generating process. From the general forecasting literature, such robustness is expected to be a rare occurrence. With the aid of a stylized macro model we are able to identify some economically relevant cases of robustness and to interpret them economically. We give an interpretation in terms of co‐breaking. The analytical results resound well with the forecasting record of a medium‐scale econometric model of the Norwegian economy.     

Bias‐corrected bootstrap prediction intervals for autoregressive model: new alternatives with applications to tourism forecasting

This paper proposes the use of the bias‐corrected bootstrap for interval forecasting of an autoregressive time series with an arbitrary number of deterministic components. We use the bias‐corrected bootstrap based on two alternative bias‐correction methods: the bootstrap and an analytic formula based on asymptotic expansion. We also propose a new stationarity‐correction method, based on stable spectral factorization, as an alternative to Kilian's method exclusively used in past studies. A Monte Carlo experiment is conducted to compare small‐sample properties of prediction intervals. The results show that the bias‐corrected bootstrap prediction intervals proposed in this paper exhibit desirable small‐sample properties. It is also found that the bootstrap bias‐corrected prediction intervals based on stable spectral factorization are tighter and more stable than those based on Kilian's stationarity‐correction. The proposed methods are applied to interval forecasting for the number of tourist arrivals in Hong Kong. Copyright © 2010 John Wiley & Sons, Ltd.     

Beating the VAR: Improving Swedish GDP Forecasts Using Error and Intercept Corrections

This paper examines the forecast accuracy of an unrestricted vector autoregressive (VAR) model for GDP, relative to a comparable vector error correction model (VECM) that recognizes that the data are characterized by co‐integration. In addition, an alternative forecast method, intercept correction, is considered for further comparison. Recursive out‐of‐sample forecasts are generated for both models and forecast techniques. The generated forecasts for each model are objectively evaluated by a selection of evaluation measures and equal accuracy tests. The result shows that the VECM consistently outperforms the VAR models. Further, intercept correction enhances the forecast accuracy when applied to the VECM, whereas there is no such indication when applied to the VAR model. For certain forecast horizons there is a significant difference in forecast ability between the intercept corrected VECM compared to the VAR model. Copyright © 2015 John Wiley & Sons, Ltd.     

准同期参数测量算法研究

在发电机并网过程中,对信号的频率、相位、幅值等参数要进行快速、准确的测量,传统的测量方法参数误差比较大.本文提出利用窗函数及频谱校正的DFT算法来对信号进行参数测量,仿真结果表明,该算法不需要对电压信号进行整周期采样,可以对频率在较大范围内变化的信号进行准确测量,从而较好的解决了由于并列双方电压的频率不断变化而引起的测量误差大的问题.     

基于Hough变换的列车客运票图像倾斜校正

为解决列车客运票防伪和自动验票中的列车客运票图像倾斜校正的问题,提出了一种基于Hough变换的列车客运票图像倾斜校正方法.该方法根据现有倾角检测算法及列车客运票图像的特点,将列车客运票图像的前景与背景分离,在对图像前景进行水平轨迹线平滑的基础上提取文本行特征线,然后采用分级Hough变换的思想实现倾角的检测,最后用直线拟合的方法实现图像的校正.实验结果表明了所提出的算法的有效性和可靠性.     

论高校图书馆对学生读者不良行为的矫正

论述了高校图书馆对学生读者不良行为矫正发生教育作用的心理学机制,分析了影响矫正教育效果的各种因素,并提出了相应的措施。     

模型势MCP应用于分子间相互作用的研究

使用模型势MCP计算了含重元素的氢键和vail der Waals相互作用体系的几何结构与结合能。结果表明，在MP2水平，应用MCP基组研究分子间相互作用时，可以使用Boys和Bernardi提出的均衡校正法进行基函数重叠误差（BSSE）校正；与同一水平的全电子基组相比，经BSSE校正后的结合能AEcP平均相对误差为5．2％，结果准确，但是BSSE普遍较大；使用MCP基组的计算时间远小于全电子基组，MCP方法的效率随原子的电子层数增加而提高。     

上海市港口发展与经济增长关系的实证研究

根据上海市1995—2012年相关统计数据,采用协整检验分析上海市港口发展与经济增长间的关系.研究表明,二者之间存在长期稳定的均衡关系.最后提出了上海市港城协调发展的对策建议.     

实验室水槽装置液位模糊控制系统的设计

介绍一种带修正因子和寻优参数的水位模糊控制系统。实验表明 ,该系统具有较强的抗干扰能力及适应内部参数变化的能力。阐述了控制方案及软、硬件的设计。