Forecasting regional house price inflation: a comparison between dynamic factor models and vector autoregressive models

This paper uses the dynamic factor model framework, which accommodates a large cross‐section of macroeconomic time series, for forecasting regional house price inflation. In this study, we forecast house price inflation for five metropolitan areas of South Africa using principal components obtained from 282 quarterly macroeconomic time series in the period 1980:1 to 2006:4. The results, based on the root mean square errors of one to four quarters ahead out‐of‐sample forecasts over the period 2001:1 to 2006:4 indicate that, in the majority of the cases, the Dynamic Factor Model statistically outperforms the vector autoregressive models, using both the classical and the Bayesian treatments. We also consider spatial and non‐spatial specifications. Our results indicate that macroeconomic fundamentals in forecasting house price inflation are important. Copyright © 2010 John Wiley & Sons, Ltd.     

Intermittent demand forecasting in the Enterprise: Empirical verification

Forecasting methods are often valued by means of simulation studies. For intermittent demand items there are often very few non–zero observations, so it is hard to check any assumptions, because statistical information is often too weak to determine, for example, distribution of a variable. Therefore, it seems important to verify the forecasting methods on the basis of real data. The main aim of the article is an empirical verification of several forecasting methods applicable in case of intermittent demand. Some items are sold only in specific subperiods (in given month in each year, for example), but most forecasting methods (such as Croston's method) give non–zero forecasts for all periods. For example, summer work clothes should have non–zero forecasts only for summer months and many methods will usually provide non–zero forecasts for all months under consideration. This was the motivation for proposing and testing a new forecasting technique which can be applicable to seasonal items. In the article six methods were applied to construct separate forecasting systems: Croston's, SBA (Syntetos–Boylan Approximation), TSB (Teunter, Syntetos, Babai), MA (Moving Average), SES (Simple Exponential Smoothing) and SESAP (Simple Exponential Smoothing for Analogous subPeriods). The latter method (SESAP) is an author's proposal dedicated for companies facing the problem of seasonal items. By analogous subperiods the same subperiods in each year are understood, for example, the same months in each year. A data set from the real company was used to apply all the above forecasting procedures. That data set contained monthly time series for about nine thousand products. The forecasts accuracy was tested by means of both parametric and non–parametric measures. The scaled mean and the scaled root mean squared error were used to check biasedness and efficiency. Also, the mean absolute scaled error and the shares of best forecasts were estimated. The general conclusion is that in the analyzed company a forecasting system should be based on two forecasting methods: TSB and SESAP, but the latter method should be applied only to seasonal items (products sold only in specific subperiods). It also turned out that Croston's and SBA methods work worse than much simpler methods, such as SES or MA. The presented analysis might be helpful for enterprises facing the problem of forecasting intermittent items (and seasonal intermittent items as well).     

Enhancing survey‐based investment forecasts

We investigate the accuracy of capital investment predictors from a national business survey of South African manufacturing. Based on data available to correspondents at the time of survey completion, we propose variables that might inform the confidence that can be attached to their predictions. Having calibrated the survey predictors' directional accuracy, we model the probability of a correct directional prediction using logistic regression with the proposed variables. For point forecasting, we compare the accuracy of rescaled survey forecasts with time series benchmarks and some survey/time series hybrid models. In addition, using the same set of variables, we model the magnitude of survey prediction errors. Directional forecast tests showed that three out of four survey predictors have value but are biased and inefficient. For shorter horizons we found that survey forecasts, enhanced by time series data, significantly improved point forecasting accuracy. For longer horizons the survey predictors were at least as accurate as alternatives. The usefulness of the more accurate of the predictors examined is enhanced by auxiliary information, namely the probability of directional accuracy and the estimated error magnitude.     

基于区间直觉模糊数的得分函数与精确函数及其应用

在模糊决策理论中,区间直觉模糊数的排序是一个非常重要的理论问题.运用得分函数和精确函数对区间直觉模糊数进行有效排序的关键是得分函数和精确函数的科学构建.本文基于得分函数和精确函数的内涵,运用概率论全概率公式思想提出了新的得分函数和精确函数,并证明了其公理化的性质.通过大量的实际数据测算与比较分析,验证了本文提出的得分函数和精确函数的科学性,从而在对区间直觉模糊数排序时更有效、更准确.     

Heterogeneous Forecast Adjustment

There is ample empirical evidence that expert‐adjusted model forecasts can be improved. One way to potential improvement concerns providing various forms of feedback to the sales forecasters. It is also often recognized that the experts (forecasters) might not constitute a homogeneous group. This paper provides a data‐based methodology to discern latent clusters of forecasters, and applies it to a fully new large database with data on expert‐adjusted forecasts, model forecasts and realizations. For the data at hand, two clusters can clearly be identified. Next, the consequences of having clusters are discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

基于动态组合残差修正的预测方法

本文建立了一种基于残差修正的组合预测方法,并基于该方法证明了针对多个单一的预测方法根据其在某个时间段的相对预测误差的大小选择组合选项可以进一步提高预测精度.提出了针对不同时间段可根据各种单项预测模型的相对预测误差的大小动态选取相对预测误差最小的两种模型构成组合残差来修正基本方法的预测误差,以提高预测精度.最后通过实际空调负荷预测对其进行了验证,结果表明这种动态组合残差修正的预测方法相对于基于多个固定单一预测方法的组合预测方法,可以进一步改善预测效果.     

Mur二阶吸收边界条件两种差分格式的比较

从理论上比较了时域有限差分法的Mur二阶吸收边界条件两种差分格式的计算精度、实现难度等,得出了直接格式计算精度较高但实现难度略大的结论.数值实验证实了上述结论.     

脉冲直接力控制简易制导弹药命中精度研究

研究了基于弹体捷联激光四象限探测器体制下,利用脉冲力进行质心控制的弹道修正技术.通过外弹道模型的建立和数值仿真,研究了弹丸落角、脉冲发动机作用位置偏离质心距离、脉冲发动机工作宽度和总冲散布等因素对于弹道修正精度的影响,对比得出了影响弹丸修正精度的主要因素,为工程实现提供理论支持.     

Non-fragile decentralized H∞ controller design for uncertain linear systems

Considering the design problem of non-fragile decentralized H∞ controller with gain variations, the dynamic feedback controller by measurement feedback for uncertain linear systems is constructed and studied. The parameter uncertainties are considered to be unknown but norm bounded. The design procedures are investigated in terms of positive definite solutions to modify algebraic Riccati inequalities. Using information exchange among local controllers, the designed non-fragile decentralized H∞ controllers guarantee that the uncertain closed-loop linear systems are stable and with H∞ -norm bound on disturbance attenuation. A sufficient condition that there are such non-fragile H∞ controllers is obtained by algebraic Riccati inequalities. The approaches to solve modified algebraic Riccati inequalities are carried out preliminarily. Finally, a numerical example to show the validity of the proposed approach is given.     

非线性微分-代数系统稳定性的几个判据

研究非线性微分－代数系统的稳定性问题,给出利用非线性函数的偏导数矩阵判别非线性微分－代数系统平衡态稳定和不稳定的几个判据,所得结果形式简洁,易于应用．最后利用例子说明所得判据的有效性