univariate time-series models
Performance of combined double seasonal univariate time series models for forecasting water consumption
... Abstract: In this article, we examine the daily water demand forecasting performance of double seasonal univariate time series models (Holt-Winters, ARIMA and GARCH) based on multi-step ahead ...
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Oil Price Forecasting Based on Various Univariate Time Series Models
... presenting time series analyses for oil prices ...of univariate time-series models were investigated: ES, HW and ...given models with actual ...competing models in ...
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Univariate Time Series Models For Fuel Price
... of Time series more essential in various fields of research, such as business, economics, medicine… ...classical time series ...traditional time series along with fuzzy ...
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Time series modelling of birth data
... multivariate models to model birth time series with other variable time series may not significantly improve the result of birth ...birth series forecast their future values may ...
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Testing for Non Linear Dependence in Univariate Time Series An Empirical Investigation of the Austrian Unemployment Rate
... linear time series models must be ...non-linear time series models must be ...model univariate time series more adequately, a larger task meets us in ...
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Univariate Time Series Analysis of Second Hand Car Importation in Zambia
... a time series prob- lem. There are several techniques that use time series but in this study we shall only concentrate on the Exponential Smoothing (ES) and Autoregressive Inte- grated Moving ...
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A COMPARATIVE STUDY OF UNIVARIATE TIME SERIES MODELLING FOR NATURAL RUBBER PRODUCTION IN MALAYSIA
... some univariate time series models, namely, the ARIMA, SARIMA and seasonal Holt-Winter’s ...the time series modelling procedures will be discussed in Section 2 while the results ...
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A Vector Auto Regressıve (VAR) Model for the Turkish Financial Markets
... use models for the analysis of multivariate time ...VAR models in economics were made popular by Sims ...the univariate autoregressive ...financial time series and for ...from ...
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SMOKE DETECTION BASED ON IMAGE PROCESSING BY USING GREY AND TRANSPARENCY FEATURES
... fuzzy time series forecasting (TSF) and several studies indicating superior performance, an appropriate computationally efficient method have not been developed to predict various time series ...
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FORECAST PERFORMANCE OF UNIVARIATE TIME SERIES AND ARTIFICIAL NEURAL NETWORK MODELS
... Precipitation time series data that exhibit seasonal, periodic variations and non-linearity is ...The models considered are Seasonal Autoregressive Integrated Moving Average (SARIMA), Fourier ...
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Forecasting Inflation and Economic Growth of Pakistan by Using Two Time Series Methods
... following models have been considered in forecasting inflation: univariate time series model (ARIMA), Phillips curve, interest rate model and the naïve ...of univariate time ...
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Semiparametric Estimation of Multivariate GARCH Models
... by univariate GARCH models, for actual and suitable transformed series, in the first step; the latter are then nonlinearly combined in the second step, according to basic properties of the covariance ...
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Likelihood Inference for Generalized Integer Autoregressive Time Series Models
... count time series models is based on thinning operators, which are replacements of the multiplication operator to maintain support on the non-negative ...count time series modeling with ...
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ARIMA and VAR Modeling to Forecast Malaysian Economic Growth
... on univariate time series via Autoregressive Integrated Moving Average (ARIMA) model and multivariate time series via Vector Autoregressive (VAR) model in forecasting economic growth in ...
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Volatility in High Frequency Intensive Care Mortality Time Series: Application of Univariate and Multivariate GARCH Models
... component univariate series of the tertiary mul- tivariate ...two univariate specifications, GARCH (1, 1) and APGARCH (1, 1) and (ii) the 4 MGARCH series (rural/regional, metropolitan, ...
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Mandelbrot's stochastic time series models
... using time series analysis, even in a controlled system like a wind tunnel one ideally wants several measurement ...one time series, then one will at least need to ensure that one uses a model ...
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Time series models of GDP: a reappraisal
... non-linear time series models of real GDP on the basis of the consideration that business-cycle features themselves should motivate a good metric for judging a macroeconomic time-series ...
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Analysis of a cross section of time series using structural time series models
... 1 ANALYSIS OF A CROSS SECTION OF TIME SERIES USING STRUCTURAL TIME SERIES MODELS by Pablo Marshall Rivera London School of Economics and Political Science 1990 Submitted to the University of London fo[.] ...
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Information Worth of MinMaxEnt Models for Time Series
... through time. In many areas from engineering to economics, patterns of time series are ...of time series. The characteristic property of a time series is that its future ...
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Forecasting Liquidity Ratio of Commercial Banks in Nigeria
... ARIMA models respectively. The models were specified as ...two models were carried out using root mean square error ...two models, we concluded that the ARFIMA model was a much better model in ...
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