SECTION A (You should attempt all 10 questions) A1. Regression analysis is ____________________________________. A) describes the strength of this linear relationship. B) describes the mathematical relationship between two variables. C) describes the pattern of the data. D) describes the characteristic of independent variable. A2. __________________ is used to illustrate any relationship between two variables. A) Histogram B) Pie chart C) Scatter diagram D) Frequency
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HTime series using Holt-Winters Forecasting Procedure Summary The Holt-Winters forecasting procedure is a simple widely used projection method which can cope with trend and seasonal variation. We can apply this method to lots of fields such as banking data analysis‚ investment forecasting‚ inventory controlling and so on. This paper shows us a practical banking credit card example using Holt-Winter method in Java programming for data forecasting. The reason we use Holt-Winter is that
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Neurocomputing 55 (2003) 307 – 319 www.elsevier.com/locate/neucom Financial time series forecasting using support vector machines Kyoung-jae Kim∗ Department of Information Systems‚ College of Business Administration‚ Dongguk University‚ 3-26‚ Pil-dong‚ Chung-gu‚ Seoul 100715‚ South Korea Received 28 February 2002; accepted 13 March 2003 Abstract Support vector machines (SVMs) are promising methods for the prediction of ÿnancial timeseries because they use a risk function consisting of the
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is not much historical data to work with. 2. Causal methods assume that demand is strongly related to a particular cause‚ such as environmental or market factors. 3. Time series methods are based on the assumption that historical patterns of demand are a good indicator of future demand‚ and that over a period of time‚ demand can be charter in three different ways: as an underlying trend (flat‚ up ‚ or down)‚ as a circle (daily‚ weekly‚ seasonally ‚ and so on)‚ and as irregular
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Forecast Error‚ Time Series Models‚ Tracking Signals ) NAME____________________ Solution True or False 1. T F According to the textbook‚ a short-term forecast typically covers a 1-year time horizon. 2. T F Regression is always a superior forecasting method to exponential smoothing. 3. T F The 3 categories of forecasting models are time series‚ quantitative‚ and qualitative. 4. T F Time-series models attempt to
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z Available online at http://www.journalcra.com INTERNATIONAL JOURNAL OF CURRENT RESEARCH International Journal of Current Research Vol. 5‚ Issue‚ 02‚ pp.248-253‚ February‚ 2013 ISSN: 0975-833X RESEARCH ARTICLE A Time Series Analysis of Wastewater Inflow of Sewage Treatment Plant in Mysore‚ India *Ayesha Sulthana‚ Balasubramanian S. and Latha K. C. Department of Water and Health‚ JSS University‚ Mysore‚ Karnataka ARTICLE INFO Article History: Received 20 November‚ 2012 Received in revised form
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independence graph for nonlinear time series and its application to international financial markets Wei Gao a‚∗ ‚ Hongxia Zhao b a b School of Statistics‚ Xi’an University of Finance and Economics‚ Xi’an Shaanxi 710061‚ China School of College English‚ Xi’an University of Finance and Economics‚ Xi’an Shaanxi 710061‚ China article info abstract Conditional independence graphs are proposed for describing the dependence structure of multivariate nonlinear time series‚ which extend the graphical
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Economics & Statistics Group Project Analysis of ORACLE Stock Price Page 1 of 38 Contents Contents.................................................................................................................................................. 1 Introduction ............................................................................................................................................ 3 Stepwise regression ......................................................................
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E cient neighbor searching in nonlinear time series analysis Thomas Schreiber Department of Theoretical Physics‚ University of Wuppertal‚ D{42097 Wuppertal July 18‚ 1996 We want to encourage the use of fast algorithms to nd nearest neighbors in k{dimensional space. We review methods which are particularly useful for the study of time series data from chaotic systems. As an example‚ a simple box{assisted method and possible re nements are described in some detail. The e ciency of the method is compared
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AN ECONOMETRIC ANALYSIS OF ENERGY CONSUMPTION AND ECONOMIC GROWTH IN TURKEY ABSTRACT It is commonly maintained that energy is an imporant input of industrial growth and‚ in this way‚ economical development. The scarcity of energy resources in the world make the relation between economic development and energy consumption more significant. In this study‚ the possible cointegration is inspected by Engle-Granger and Johansen Tests and the direction of the causality is searched by Granger causality
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