Comparison of the effectiveness of forecasts obtained by means of selected probability functions with respect to forecast error distributions

The forecasting of sales in a company is one of the crucial challenges that must be faced. Nowadays, there is a large spectrum of methods that enable making reliable forecasts. However, sometimes the nature of time series excludes many well-known and widely used forecasting methods (e.g., econometric models). Therefore, the authors decided to forecast on the basis of a seasonally adjusted median of selected probability distributions. The obtained forecasts were verified by means of distributions of the Theil U² coefficient and unbiasedness coefficient.     

桑弘羊经济立法思想探微

西汉中期,时为掌管封建中央财政事务大臣的桑弘羊在坚持先秦法家思想的基础上,先后推行和提出了大力发展官商,打击私商,实施盐铁专卖,均输平准等一系列的经济立法措施和财政政策,它是汉王朝社会经济方式由自由放任转向国家干预控制的重要转折,其思想对加强封建中央财政管理,充实封建国家财政收入和缓解社会财政危机发挥了重要的作用,其许多首创的理论和实践被后代各封建王朝的理财大臣看作是可望不可及的成功的财政典型,且为当时世界上不少国家所推崇和采用。研究这一中国古代法制史上的重要成果,对思考我们现实社会财政经济的改革发展有宝贵的借鉴意义。     

众包标注质量控制研究

众包是近年来流行的一种分布式商业模式,采用众包方式获取标注是一种快速廉价获取海量数据标签的有效方式,由于众包平台中普遍存在不认真完成任务的作弊用户,众包标注质量难以保证.为有效提高众包标注准确性,通过学习标注者的可靠性,实现基于标注者的可靠性进行动态任务分配,采用贪婪的预测模型实现对多个标注者提交的标签进行聚集,获得高质量的众包标注结果.实验结果表明,该方法能获得比基准算法更高的标注准确性,有效实现众包标注质量控制.     

以知识管理解决政府信息失真问题的对策与建议

解决政府信息失真的问题,是提高政府管理能力和管理效率的重要途径。要从根本上真正解决政府信息失真的问题,光靠技术上的信息管理是不够的。文章指出运用知识管理理论来解决政府信息失真问题可能是一条有效途径,运用知识管理理论,建立起学习型政府,明确以知识管理解决政府信息问题的原则,并采取一系列切实有效的对策和措施从根本上解决政府信息失真。     

Combining forecasts of electricity consumption in China with time-varying weights updated by a high-order Markov chain model

Electricity consumption forecasting has been always playing a vital role in power system management and planning. Inaccurate prediction may cause wastes of scarce energy resource or electricity shortages. However, forecasting electricity consumption has proven to be a challenging task due to various unstable factors. Especially, China is undergoing a period of economic transition, which highlights this difficulty. This paper proposes a time-varying-weight combining method, i.e. High-order Markov chain based Time-varying Weighted Average (HM-TWA) method to predict the monthly electricity consumption in China. HM-TWA first calculates the in-sample time-varying combining weights by quadratic programming for the individual forecasts. Then it predicts the out-of-sample time-varying adaptive weights through extrapolating these in-sample weights using a high-order Markov chain model. Finally, the combined forecasts can be obtained. In addition, to ensure that the sample data have the same properties as the required forecasts, a reasonable multi-step-ahead forecasting scheme is designed for HM-TWA. The out-of-sample forecasting performance evaluation shows that HM-TWA outperforms the component models and traditional combining methods, and its effectiveness is further verified by comparing it with some other existing models.     

Keeping an Uphill Edge

Abstract

Several behaviors in a ski shop were identified as being deficient using Austin's Performance Diagnostic Checklist (2000) and Daniels and Daniels' PIC/NIC Analysis (2004). During a 4-week baseline, 7 cleaning behaviors were monitored and 5 were subsequently targeted in an intervention package using an ABC design. The intervention included: a task clarification session, a posted behavioral checklist, graphic feedback of the group's performance for the previous week, and daily task-specific feedback. Immediately after the checklist was posted, the frequency of employee cleaning behaviors increased 52%. Cleaning behaviors increased an additional 12% after the implementation of daily task-specific feedback. Results suggest the interventions generalized to the 2 cleaning behaviors not mentioned in the task-clarification session.     

Multiperiod Forecasts of Interest Rates

The accuracy of forecasts of interest rates over different forecast horizons and time periods is examined. The results indicate a deterioration in “absolute” forecast accuracy measured by the mean absolute error and the root mean squared error but no decrease in “relative” accuracy measured by the Theil coefficient with an increase in the forecast span. The results also indicate a decline in accuracy in periods of volatile interest rates. Support is found for the hypothesis that the ratio of the variability of predicted changes to that of actual changes falls with an increase in the forecast horizon.     

A comparison of test statistics for the recovery of rapid growth‐based enumeration tests

This paper considers five test statistics for comparing the recovery of a rapid growth‐based enumeration test with respect to the compendial microbiological method using a specific nonserial dilution experiment. The finite sample distributions of these test statistics are unknown, because they are functions of correlated count data. A simulation study is conducted to investigate the type I and type II error rates. For a balanced experimental design, the likelihood ratio test and the main effects analysis of variance (ANOVA) test for microbiological methods demonstrated nominal values for the type I error rate and provided the highest power compared with a test on weighted averages and two other ANOVA tests. The likelihood ratio test is preferred because it can also be used for unbalanced designs. It is demonstrated that an increase in power can only be achieved by an increase in the spiked number of organisms used in the experiment. The power is surprisingly not affected by the number of dilutions or the number of test samples. A real case study is provided to illustrate the theory. Copyright © 2013 John Wiley & Sons, Ltd.     

An approximation for the hotelling-lawley trace in the noncentral case

A procedure for estimating power in conjunction with the Hotelling-Lawley trace is developed. By approximating a non-central Wishart distribution with a central Wishart, and using McKeon's (1974) F-type approximation, a relatively simple procedure for obtaining power estimates is obtained. The accuracy of the approximation is investigated by comparing the approximate results with those for a wide range of conditions given in Olson's (1973) extensive Monte Carlo study. Siotani's (1971) asymptotic expansion is used to provide further comparative assessments. It is demonstrated that the approximation is of sufficient accuracy to be used in practical applications.     

Effects of Feedback Delivery Requirements on Accuracy of Observations

ABSTRACT

Feedback is often used in Organizational Behavior Management to improve employee performance. Accurate feedback results in greater improvements in performance and accurate observations enable accurate feedback. However, employees may find providing feedback to peers aversive. The present study contrived a method to evaluate whether instructing individuals to deliver feedback following observations impacted the accuracy of those observations. Five college-aged participants were exposed to a counterbalanced ABAB design. In the observation-only condition (Condition A) participants conducted observations of confederate posture, scoring whether the confederate’s feet and back were “safe” or “at risk.” In the required-feedback condition (Condition B) participants observed and collected data identically to phase A, but were additionally instructed to deliver feedback regarding confederate postures following each session. The results show that all five participants demonstrated higher accuracy of observations in the observation-only condition. Factors potentially influencing lower accuracy when feedback was required are discussed.