time series modeling methodology
Time series modeling for syndromic surveillance
... systematic methodology described here can be generalized to other healthcare settings for developing biosurveillance systems that detect anomalous increases in healthcare utilization ...
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Hybrid of ARIMA-GARCH modeling in rainfall time series
... empirical modeling of hydrological time series, the focus was on modeling and predicting the mean behavior of the time series through conventional methods of an Autoregressive ...
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Factor modeling for high dimensional time series
... functional time series has been of a more theoretical nature; see ...functional series (Part IV of Ferraty & Vieu ...curve series in this chapter, the methodology may be extended to ...
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Identification and Modeling of Outliers in a Discrete - Time Stochastic Series
... The importance of detecting and estimating the effects of outliers can never be overemphasized. According to Battaglia and Orfei (2002), outliers may have a significant impact on the results of standard ...
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Modeling and prediction of time-series of monthly copper prices
... Long-term forecasts are more unreliable than short-term ones and it should be remembered that no forecasting methodology will be fully accurate all of the time so there are risks associated with using them. ...
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Modeling Monthly Rainfall Time Series Using Ets State Space And Sarima Models
... rainfall time series; and compare the performance of Seasonal ARIMA models and State space models with applications to two monthly rainfall series in peninsular ...contemporaneous time ...
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Modeling and Forecasting Africa's GDP with Time Series Models
... The first difference of the data is not stationary for Angola, Gabon, Kenya, Nigeria, South Africa, Sudan and Tanzania. Therefore, we perform the second difference and the second difference render the data stationary. ...
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Trend analysis of extreme precipitation in the Northwestern Highlands of Ethiopia with a case study of Debre Markos
... value modeling. After reviewing the statistical methodology on extremes, this paper presents an analysis based on the generalized extreme value modeling with daily time series of ...
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Time Series Modeling and Forecasting of CPI of Bangladesh
... Time series data is very important in the case of financial development of any ...with time series data. This study is consists of time series modeling and forecasting of ...
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Box Jenkins’ Methodology in Predicting Maternal Mortality Records from a Public Health Facility in Ghana
... Box-Jenkins methodology to model the maternal mortal- ity cases recorded at KATH, Kumasi, Ghana, using data from 2000 to ...The time series modeling was employed by first assessing the ...
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Time series outlier detection: a new non parametric methodology (washer)
... among time series: in figures 1, 2 and 3 there are some examples of the concept of “similar behav- iour” for some time series considered at t 1, 2,3 ...
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Sugarcane transportation process modeling by time series approach
... The curve in Fig.9 illustrated that instability was retained and oscillations occurred within service interval time. The unloading of tractor drawn carts terminates in sugarcane factory equipment failure ...
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The World’s Largest Lakes Water Level Changes in the Context of Global Warming
... simultaneous series of water level observa- tions, both for the period of the stationary and non-stationary ...the time limit of the beginning of climate change in years as it is a continuous process that, ...
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The Comparative Comparison of Exchange Rate Models
... economic series which have unequalized variance, but in the case of non-routine events such as severe changes of variable drift, their efficiency will considerably decreased (Abonori and Khanalipoor, ...
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SARS Time Series Modeling and Spatial Data Analysis
... According to SARS infectious analysis, it itself infectious, the virus-carrying cases and cases of contact with the source of infection, in order to properly control the source of infection, approach is timely isolation ...
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Autoregressive nonlinear time-series modeling of traffic fatalities in Europe
... safety time-series are often small, such models are suitable for this ...the time-intervals should be such that they provide adequate data for the model estimation and still allow for a reasonable ...
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Time series modeling and forecasting of the consumer price index in Belgium
... As shown above, the mean is positive, i.e. 60.763. The minimum is 16 while the maximum is 113. The skewness is -0.023507 and the most striking characteristic is that it is positive, indicating that the B series is ...
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Methodology and reporting characteristics of studies using interrupted time series design in healthcare
... Rigorous evaluations are the cornerstone of evidence- based healthcare. The gold standard for evaluating the causal effect of an intervention is a randomised con- trolled trial (RCT). However, RCTs do have limitations, ...
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Financial-Economic Time Series Modeling and Prediction Techniques – Review
... Financial-economic time series distinguishes from other time series because they contain a portion of ...in time series makes them non- linear, which on the other hand suggests ...
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Detection and predictive modeling of chaos in finite hydrological time series
... is mixed with the same underlying chaotic signal. Several properties are observed. First, the saturation value of the cor- relation exponent increases as the white noise component (σ ) increases. Second, a threshold ...
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