Hierarchical clustering of spatially correlated functional data

Classification problems of functional data arise naturally in many applications. Several approaches have been considered for solving the problem of finding groups based on functional data. In this paper, we are interested in detecting groups when the functional data are spatially correlated. Our methodology allows to find spatially homogeneous groups of sites when the observations at each sampling location consist of samples of random functions. In univariable and multivariable geostatistics, various methods of incorporating spatial information into the clustering analysis have been considered. Here, we extend these methods to the functional context to fulfil the task of clustering spatially correlated curves. In our approach, we initially use basis functions to smooth the observed data, and then, we weight the dissimilarity matrix among curves by either the trace‐variogram or the multivariable variogram calculated with the coefficients of the basis functions. This paper contains a simulation study as well as the analysis of a real data set corresponding to average daily temperatures measured at 35 Canadian weather stations.     

End-User Contribution to Logistics Value Co-Creation: A Series of Exploratory Studies

ABSTRACT

Recently, retailers have been investing in technology-based platforms such as mobile applications to involve more of their customers in logistical value co-creation activities. Therefore, it would be important to guide these efforts by providing the retailers with a list of various consumer logistics value co-creation activities and help them better organize their technological investments by categorizing these functions. The objective of this study is to explore the logistics activities through which the end users can contribute to co-creation of value based on the notions of Service-Dominant Logic. A series of 4 exploratory survey studies revealed 10 end-user logistics functions and important implications for practice.     

Determinants of Consumer Responses to Direct Marketing Media

Abstract

This study examined consumer propensity to respond to direct marketing offers made via catalogs, direct mail, and direct response TV. A comparison of the relative importance of marketer's reputation, advertising exposure frequency, and the product offer revealed that the latter was the most important determinant of consumer response frequency. Marketer's reputation was found to be more important for direct response TV and less important for catalog advertising: neither did high frequency of media exposure appear to impact on responses to direct mail and direct response television. The findings suggest that the maximization of reach rather than frequency could possibly be the primary media communication goal for selling products through direct mail and direct response television.     

论思想政治理论课在高校学风建设中的作用

学风建设是高校的永恒主题,是一项复杂的系统工程。充分发挥思想政治理论课的导向、推动、协调、激励等作用,对于不断改善高校的学风建设,提高教育教学质量,实现学校更好更快发展,有着十分重要的作用。     

论如何当好机关办公室主任

文章主要对新形势下如何当好机关单位办公室主任提出见解。     

如何提高学生学习实变函数与泛函分析的兴趣

本文分析了实变函数与泛函分析课程的特点,提出一些提高教学效果的思路与方法,用于激发学生学习的兴趣,使得抽象难教的实变函数与泛函分析课程能够让学生易于接受。     

Assessing the Effect of Data Collection Mode on Measurement

This paper discusses the challenges in assessing the effects of mixed modes on measurement. We briefly review theories about why different modes of data collection can lead to differences in survey responses and statistical methods typically used to assess mode effects. We then discuss the challenges, including which mode effects are identified, how to test for mode effects, and whether these would affect substantive conclusions. The issues raised are illustrated with examples from the European Social Survey, which is conducting a programme of experimental research to inform decisions about whether to use mixed modes of data collection. The paper concludes with general implications for mixed modes research.     

Joint analysis and estimation of stock prices and trading volume in Barndorff-Nielsen and Shephard stochastic volatility models

We introduce a variant of the Barndorff-Nielsen and Shephard stochastic volatility model where the non-Gaussian Ornstein–Uhlenbeck process describes some measure of trading intensity like trading volume or number of trades instead of unobservable instantaneous variance. We develop an explicit estimator based on martingale estimating functions in a bivariate model that is not a diffusion, but admits jumps. It is assumed that both the quantities are observed on a discrete grid of fixed width, and the observation horizon tends to infinity. We show that the estimator is consistent and asymptotically normal and give explicit expressions of the asymptotic covariance matrix. Our method is illustrated by a finite sample experiment and a statistical analysis of IBM? stock from the New York Stock Exchange and Microsoft Corporation? stock from Nasdaq during a history of five years.     

Do Sexy Cover Models Increase Magazine Sales?

Abstract

In the competitive struggle to increase circulation, mainstream men's magazines (such as Details, Maxim, Esquire) are featuring sexually attractive people on their covers. This article reports the findings of a study designed to determine if the sexual response evoked by cover models is related to interest in the magazine and purchase intention. Findings suggest that sexual attractiveness of the cover model and sexual arousal were related to interest in the magazine, but not purchase intention. Although no gender differences emerged, those with a positive sexual response to the cover person were more interested in the magazine. These results suggest that sexy cover models may be most effective for attracting attention to, and interest in, the magazine at the newsstand, but that feature articles have greater impact on purchase decisions.     

A neural network demand system with heteroskedastic errors

In this paper we consider estimation of demand systems with flexible functional forms, allowing an error term with a general conditional heteroskedasticity function that depends on observed covariates, such as demographic variables. We propose a general model that can be estimated either by quasi-maximum likelihood (in the case of exogenous regressors) or generalized method of moments (GMM) if the covariates are endogenous. The specification proposed in the paper nests several demand functions in the literature and the results can be applied to the recently proposed Exact Affine Stone Index (EASI) demand system of [Lewbel, A., Pendakur, K., 2008. Tricks with Hicks: The EASI implicit Marshallian demand system for unobserved heterogeneity and flexible Engel curves. American Economic Review (in press)]. Furthermore, flexible nonlinear expenditure elasticities can be estimated.