In this study, we deal with a method to specify simultaneously both the whole Asian path diagram and the diagrams which express the differences between the countries with regard to the model of second-order factor analysis for brand evaluation. Utilizing “Brand Asia”, a survey project investigating brand images of 60 global brands over 12 countries in Asia, we also verify its efficacy. Although the conventional methods allow us only to analyze either the overall Asia or the differences between the countries, the Bayesian approach enables us to analyze both simultaneously. Besides, by interpreting the hyperparameters of prior distribution aggressively, it also enables us to clarify the proportion of the university overall Asia to the diversity in each country and the unstable indexes for the model.
We give a new graphical method to test for normality based on an approximate joint probability density function of the sample skewness and kurtosis. This approximation is initiated by Shenton & Bowman (1977). For Fisher's iris data, our examples are shown in comparison with qqplot and Shapiro-Wilk test. Computer simulations are conducted as follows : Type one errors are evaluated in order to show the validity of the proposed reject region. Powers are calculated against the samples drawn from contaminated normal distributions. We show our method has the same power as Shapiro-Wilk test excluding the case of some parameters. Therefore, our method is advantageous to make graphical interpretation in testing for normality.
The receiver operating characteristic (ROC) curve is a currently well-developed statistical tool for characterizing accuracy of medical diagnostic tests. In recent years, several authors suggest approaches referred to as ROC regression models in order to evaluate effects of factors influencing accuracy of diagnostics. Rodríguez-Álvarez et al. (2011b) suggested an inference process of ROC regressions which formulate influences of some factors in the framework of a generalized additive model (GAM). In their approach, local linear kernel smoothers based on the cross-validation (CV) criterion are used to estimate smoothing functions. In this report, we propose an approach with penalized splines based on the restricted maximum likelihood (REML) for the function estimation. We give a detail of our method, and through a simulation, show that this approach gives better inference performance than existing methods, particularly in the small sample.
We study the design of recommendation system based on the customer's interest and purchase individuality. A study on design of recommendation system is very important role in the field of e-commerce business. In this paper, from the standpoint of FRM analysis, we focus on the customer's purchase cycle. We estimate the customer's purchase cycle using “the number of browse items" and “elapsed time from last browse". As a result, our method shows that most effective purchase cycle is nine days. In addition, it was found that customers buy the same color items that bought in same item category at a time in the past.
Association analysis is analysis technique for transaction data that etracts the patterns of what items one customer purchases together. By limiting the analysis to specific group of customers, we may extract a rule not among the association rules for the whole. In this study, we used this method, which we refer to as “Conditioning Association Rules”, to analyze trends in purchases of preferred customers characteristics extracted as Conditioning Association Rules for each group. In addition, we analyzed generational and gender differences in purchase trends.
The information that customer data usually provide is the personal surface information such as gender, age and hometown, but we can also obtain personal internal information by analyzing questionnaire responses. In this paper, we propose a visualization method that combines Association Analysis with Correspondence Analysis, that can find differences in six layers of internal characteristic.
In this paper, we describe the design and implementation of our visualization software and characteristics of some products in the scan panel data set that was provided for the date competition organized by the Joint Association Study Group of Management Science. Our software can display time series data of buying information with the animation. The buying information is aggregated values by the gender and the generation of monitors and supplier, are shown by the expanded parallel coordinate plot. Our software displays traces to distinguish the direction and the amount of change with the screen shot of the animation. We had implemented our software using the Java language and MySQL.
April 03, 2017 There had been a system trouble from April 1, 2017, 13:24 to April 2, 2017, 16:07(JST) (April 1, 2017, 04:24 to April 2, 2017, 07:07(UTC)) .The service has been back to normal.We apologize for any inconvenience this may cause you.
May 18, 2016 We have released “J-STAGE BETA site”.
May 01, 2015 Please note the "spoofing mail" that pretends to be J-STAGE.