presents a new adaptive method‚ which enables a smoothing parameter to be modelled as a logistic function of a user-specified variable. The approach is analogous to that used to model the time-varying parameter in smooth transition models. Using simulated data‚ we show that the new approach has the potential to outperform existing adaptive methods and constant parameter methods when the estimation and evaluation samples both contain a level shift or both contain an outlier. An empirical study‚ using the
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1. Contexts: Saint-Josse-ten-Noode‚ Saint-Gilles and Watermael-Boitsfort This first chapter is dedicated to characterising the research fields in terms of demographics and local diversity management measures. As long as it provides the context in which the institutional discourse is produced‚ the description of these environments is an important prerequisite to accurately analyse the institutional discourse on multiculturality. 1.1. Demographics Multiculturality‚ defined as the cohabitation of
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Executive Summary Dumitri Mironescu is the owner of a limousine company in Las Vegas which currently consists of 17 vehicles. During the year of 2012‚ Dumitru decided that it was time to replace three of the company’s 17 vehicles. In addition‚ Dumitru wanted to add two new vehicles to his fleet of limousines. Dumitru submitted a business plan to the bank to finance his purchases. After reviewing his business plan‚ the bank was not comfortable with the company’s revenue forecast and needed further
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researcher specify the constrains on the marketing research activity‚ identify the data needed for marketing actions‚ and determine how to collect the data. The third step is collecting relevant information which can be used to make a rational‚ informed marketing decision. Secondary data and primary data are considered in collecting relevant information. The fourth step is developing findings which involves analyzing the data carefully and presenting the findings that should be clear and understandable
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software BI as the best. Both SiSense and Birst have key features with Data collection‚ 3rd-party data integration‚ Data visualization‚ Customizable dashboards‚ Self-service‚ Mobile accessibility‚ Adhoc analytics and reports. The only major difference between two of these tools are SiSense has a key feature with SaaS hybrid platform and Birst has
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c. Which averaging period provides a better historical fit based on the MAD criterion? [pic] 2. Refer to the data provided in problem 1. Use a 3-period weighted moving average to forecast the population of the United States in 2003. Use Solver to determine the optimal weights based on minimizing the MAD criterion. [pic] 3. Refer to the data provided in problem 1. a. Use exponential smoothing with a smoothing constant of 0.5 to forecast the population of the
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Researchers who wish to conduct study in the field of data mining will benefit from this study. Students which are not sure of the course recommended by the National Career Assessment Exam will benefit from this study. It will provide a quick assessment to the students by just inputting the course recommended by the National Career Assessment Exam together with the student’s academic record during high school. The system will use the principles of data mining in order to forecast whether the course will
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popular or convenient places close to our physical location or even remotely check in to restaurants. These types of applications when accessed on a desktop system are bland and less of an experience. While there are some limitations to the scope of data that can be accessed and delivered to a mobile‚ equally there are a host of features‚ be it GPS or barcode scanning‚ which can open up new possibilities for how mobiles can deliver a fast‚ efficient and dynamic user experience. CPU performance tends
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forecasting model(s) |Description |Qualitative Approach |Quantitative Approach | |Applicability |Used when situation is vague & little data exist |Used when situation is stable & historical data | | |(e.g.‚ new products and technologies) |exist | | | |(e
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non-sample benchmark (Doane & Seward‚ 2007). The learning team has chosen to create a hypothesis testing using the wages and wage earners data set. The learning team has developed one business research question from which the team will formulate a research hypothesis. The business research question and testing simply involves creating two separate groups of the data set‚ and testing whether a difference in the mean of the earnings in both the older group‚ ages 42-64 and the younger group‚ ages 18-41
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