探究“新零销售”模式下影响销售量的相关因素

在新零销售模式的推动下,客户越来越倾向于消费个性化的商品。为了精准预测客户的消费需求,论文以单款单色产品为研究对象,通过建立多元回归分析的数学模型,来探究影响商品销售量的相关因素。经过分析发现,除了一些定性因素外,定量因素对销售量也产生了一定的影响,其中实际花费总金额、实际销售单价、库存数等定量因素对销售量的影响较大,且各个变量之间具有相关性,所以电商平台应特别关注这三个变量的影响。     

Multiple aspect testing for case-control designs

When testing for the equality of two distributions in a case-control design with treatment effects presumed to act possibly on more than one aspect, different tests may be properly considered for testing for different features of a null hypothesis, leading to the multiple aspect testing issue. Two different aspects are therefore of interest: the location-aspect, based on the comparison of location indexes, and the distributional-aspect, based on the comparison of the empirical distribution functions. A simulation study shows that the combined testing procedure exhibits a good robust overall performance, and an application in biomedical research is also presented.     

Scientific methods in finance

Computer software can easily produce many financial models with technical skill, but investigators need to interpret and adapt computer output. Such analysis requires a deep knowledge of scientific fundamentals. We argue that an evidential perspective is more appropriate than a decision framework for model selection. We discuss four necessary conditions for any scientific investigation: observables, interpretables, replicables, and robustness in the context of examples familiar to finance professionals. Carefully planning the design of an experiment is the best way to address many econometric maladies. Furthermore, we emphasize the need for more sensitivity testing and for independent replication of empirical results within the finance profession.     

Inference with Dependent Data in Accounting and Finance Applications

We review developments in conducting inference for model parameters in the presence of intertemporal and cross‐sectional dependence with an emphasis on panel data applications. We review the use of heteroskedasticity and autocorrelation consistent (HAC) standard error estimators, which include the standard clustered and multiway clustered estimators, and discuss alternative sample‐splitting inference procedures, such as the Fama–Macbeth procedure, within this context. We outline pros and cons of the different procedures. We then illustrate the properties of the discussed procedures within a simulation experiment designed to mimic the type of firm‐level panel data that might be encountered in accounting and finance applications. Our conclusion, based on theoretical properties and simulation performance, is that sample‐splitting procedures with suitably chosen splits are the most likely to deliver robust inferential statements with approximately correct coverage properties in the types of large, heterogeneous panels many researchers are likely to face.     

Why are there time-varying comovements in the European stock market?

This paper analyzes the dynamics of pair comovements between different domestic European stock market returns (Spain, France, Germany, Switzerland and the United Kingdom) seeking to check whether there is a unique source of risk driving those dynamics. Once it is shown that the comovements are time-varying, the question is to find whether a global index such as the Euro Stoxx can be considered the main source of risk. To that end we estimate and test for time-varying global pair covariances and for time-varying remaining pair covariances once the effect of the Euro Stoxx is removed. The empirical results are obtained considering locally stationary variables, a family that includes variables with first and second time-varying moments. Under that framework time-varying means and covariances can be estimated using a spline-based procedure and Wald-type statistics can be computed to test for time-variations. A simulation study shows that the role of the mean estimation part is crucial to the good performance of the tests for second moments. The empirical results evidence that all global pair covariances for the European countries analyzed are time-varying, but also that the Euro Stoxx can be considered as the driving source of risk for these time-varying dynamics. This conclusion is very useful for modeling purpose and financial strategies. Finally, we repeat the analysis considering the Nasdaq as an alternative global index and find that it explains only a small part of the dynamics in the European pair comovements.     

材料试验检测技术在公路工程中的应用分析

试验检测技术作为当前对公路路面施工中工程质量保证当中的重要环节,对路面工程施工的质量有着重要的作用。本文以公路路面养护中的主要材料试验检测方法和指标作为基础,从材料试验检测的作用和实际应用对其进行阐述,并指出在养护中运用这些指标和方法的重要性。     

Does institutional quality resolve the Lucas Paradox?

The Lucas Paradox observes that capital flows predominantly to relatively rich countries, contradicting the neoclassical prediction that it should flow to poorer capital-scarce countries. In an influential study, Alfaro, Kalemli-Ozcan, and Volosovych (AKV) argue that cross-country variation in institutional quality can fully explain the Paradox, contending that if institutional quality is included in regression models explaining international capital inflows, a country’s level of economic development is no longer statistically significant. We replicate AKV’s results using their cross-sectional IFS capital flow data. Motivated by the importance of conducting inference in statistically adequate models, we focus on misspecification testing of alternative functional forms of their empirical model of capital flows. We show that their resolution of the Paradox relies on inference in a misspecified model. In models that do not fail basic misspecification tests, even though institutional quality is a significant determinant of capital inflows, a country’s level of economic development also remains a significant predictor. The same conclusions are reached using an extended dataset covering more recent IFS international capital flow data, first-differenced capital stock data and additional controls.     

检测机构仪器设备档案管理初探

阐述了检测机构如何根据《实验室资质认定评审准则》要求,确定仪器设备档案的归档范围、归档内容,并通过建立实验室管理系统使仪器设备档案管理实现数字化、网络化,还对仪器设备档案的归档流程等内容进行了探讨。     

Extreme Value Theory and Statistics of Univariate Extremes: A Review

Statistical issues arising in modelling univariate extremes of a random sample have been successfully used in the most diverse fields, such as biometrics, finance, insurance and risk theory. Statistics of univariate extremes (SUE), the subject to be dealt with in this review paper, has recently faced a huge development, partially because rare events can have catastrophic consequences for human activities, through their impact on the natural and constructed environments. In the last decades, there has been a shift from the area of parametric SUE, based on probabilistic asymptotic results in extreme value theory, towards semi‐parametric approaches. After a brief reference to Gumbel's block methodology and more recent improvements in the parametric framework, we present an overview of the developments on the estimation of parameters of extreme events and on the testing of extreme value conditions under a semi‐parametric framework. We further discuss a few challenging topics in the area of SUE. © 2014 The Authors. International Statistical Review © 2014 International Statistical Institute     

有效提升粮油检测数据的准确度

本文主要探讨粮油检测数据的科学性和准确性,包括粮油样品的扦取、检测误差的控制、检测质量体系的运行、检测数据处理的原则和检测报告的编制等。