extended time-series model
An Empirical Time Series Model of Economic Growth and Environment
... (1956) model to estimate the impact of water pollution on per worker output for New ...growth model in which the factor accumulation can only explain about half the variations in the growth ...growth ...
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Research On Stochastic Forecasting Discharge Level Time Series Data Using Extended Linear Group And Extended Semi-Group Approach
... Markovian model make the advantages of correlation between data and can concentrate the characteristics of stochastic ...with Time Series Models (Bell, ...grains time series ...
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A vector auto-regressive model for onshore and offshore wind synthesis incorporating meteorological model information
... and extended in a novel way to incorporate o ff shore time series from a pan-European meteorological model called COSMO, with onshore wind speeds from the MIDAS dataset provided by the British ...
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Modelling financial time series with SEMIFAR GARCH model
... 0) model and the fractional autogressive process (Hosking, 1981, Granger and Joyeux, ...financial time series. Often financial time series exhibit conditional heteroskedasticity, ...
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Fiscal policy and the Great Recession in the euro area
... the extended version of the NAWM, we use quarterly time series for 17 out of the 18 macroeconomic variables used in the estimation of the baseline model: real GDP, private consumption, ...
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Extended Wiener Measure by Nonstandard Analysis for Financial Time Series
... We next consider an extension of the multi-steps ( nT steps) binomial model to the infinitesimal scale model from the view point of the non-standard analysis. The binomial distribution is calculated by the ...
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Probing the linearity and nonlinearity in the transitions of the atmospheric circulation
... linear model on the grounds that linear cor- relations capture only linear ...be extended to time series, x(t ), by considering inputs as past values of the time series, and ...
5
Application of GAs to Determine the Parameters of a Time Series Model
... Our application examples helped us realize that the coding of data for model a problem is complex. On the other hand, we also saw difficulties effectively choose good parameter for the various operators (mutation, ...
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The Exponential Model for the Spectrum of a Time Series: Extensions and Applications
... for time series methods, although most often annual sunspot series are analysed (see Xia and Tong, 2011, section ...The series is compiled by the Solar Influences Data Analysis Center in ...
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Model Metric Co-Learning for Time Series Classification.
... to model indi- vidual image sequences, suggested three novel distances be- tween the models, in particular: principal angles between spe- cific subspaces derived from the models, Martin and geodesic ...existing ...
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Application of Gas to Determine the Parameters of a Time Series Model
... However, as she deals with much more complicated situations, it is difficult to grasp the principles of this technique, as well as the limits of its application. In addition, the cost of me- Box-Jenkins method in a given ...
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Transaction taxes, traders’ behavior and exchange rate risks
... baseline model without transaction taxes produce time series with realistic time series properties like in empirical exchange rate ...the model is capable to reproduce stylized ...
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A diagnostic for the general linear model : an application to Time Series
... where is a correlation parameter and an innovation outlier, A, is intro duced at time k. The set of random variables are independent and identically distributed such th at e* ~ iV(0,a^) Vi 6 The parameters ^ and ...
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Forecasting Model For Enrolment Combining Weighted Fuzzy Time Series And Fourier Series Transform
... fuzzy time series to forecast real problems, such as forecasting stock market, temperature prediction, forecasting enrolments, disease diagnosing, ...Traditionally, time series forecasting ...
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Forecasting Liquidity Ratio of Commercial Banks in Nigeria
... modeling time series in the presence of long memory, the Autoregressive fractionally integrated moving average (ARFIMA) model is ...are time series models that generalize ARIMA models ...
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Dynamical process upscaling for deriving catchment scale state variables and constitutive relations for meso scale process models
... surface model element extends over the width of the hills- ...the model equations, which are now standard ones for most physically based models, are not presented ...
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Auto-Regressive Integrated Moving-Averages Model For Daily Rainfall Forecasting
... AR model is used for the statistical calculations of a time series; hence estimating future values on the basis of the weighted sum of the previous ...The model shows that the resulting values ...
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Predicting Crimes Using Time Series Model and ARCGIS Software
... Crime prediction may be testing in three different areas: temporal, spatial and temporal – spatial. Prediction of temporal - special crimes is a new type and it has been popular among cerographists. Crime analysis using ...
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Cosinor-based rhythmometry
... estimate of uncertainty (experimental error or noise) used to derive statistical signifi- cance (P-values) and confidence intervals. Noise originates from variations in the bio- logical system considered not to be part ...
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The Intelligent Forecasting Model of Time Series
... dividing time series in specific lags and exploring the unique and best predicting parameters model valid for each lag (for all sensors in closely area) of the time ...of time ...
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