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Hamilton, J.D. (1994) Time Series Analysis. Princeton University Press, Princeton.
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has been cited by the following article:
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TITLE: The Application of Time Series Modelling and Monte Carlo Simulation: Forecasting Volatile Inventory
Biomedical & Life Sciences
AUTHORS: Robert Davies, Tim Coole, David Osipyw
Business & Economics
KEYWORDS: Forecasting, Time Series Analysis, Monte Carlo Simulation
Chemistry & Materials Science
JOURNAL NAME: Applied Mathematics, Vol.5 No.8, May 5, 2014
Computer Science & Communications
ABSTRACT: During the assembly of internal combustion engines, the specific size of crankshaft shell bearing is not
Requirements
known until the crankshaft is fitted to the engine block. Though the build requirements for the engine are consistent,
Earth & Environmental Sciences
the consumption profile of the different size shell bearings can follow a highly volatile trajectory due to minor variation
Engineering
in the dimensions of the crankshaft and engine block. The paper assesses the suitability of time series models
Medicine & Healthcare
including ARIMA and exponential smoothing as an appropriate method to forecast future requirements. Additionally, a
Physics & Mathematics
Monte Carlo method is applied through building a VBA simulation tool in Microsoft Excel and comparing the output to
Social Sciences & Humanities
the time series forecasts.
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