Forecasting models
A Survey of Selected Grey Forecasting Models with Application to Medical Tourism Forecasting
... Systems Forecasting models. The original Grey GM(1,1) Forecasting model, introduced by Deng [1] [2] together with an improved Grey GM(1,1) model proposed by Ji et al ...the models using four ...
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HIV -Forecasting Models of CD4 Count
... the models clearly and precisely using different clinical and biological parameters, which has been very well-understood in connection to dynamics of HIV –diseases, such as increase in CD4 count after inception of ...
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Evaluating Density Forecasting Models
... Evaluation of predictions is an important step in any forecasting process. For point estimates this is a straightforward process that typically involves determining the Euclid- ean distance between the predicted ...
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Multivariate Bayesian forecasting models
... is given in Section 2.1, the updating recursions are provided in Sction 2.2, time invariant interpretation of the parameters and model building from simple components are the topics in S[r] ...
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Judgmental Selection of Forecasting Models
... (judgmental) forecasting model selection process, providing clear guidance of a judgmental selection to be driven from prevailing components (most notably trend and seasonality) as per- ceived by the user ...
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An investigation into the properties of Bayesian forecasting models
... A number the of and other single state of on line variance and tested on estimation methods are proposed The methods are shown to be robust artificial and real data.. and the lead to imp[r] ...
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Developing and Evaluating SIMM Forecasting Models
... Also, we see from the figures that, as the composition of the counterparty portfolios becomes more balanced between payer and receiver swaps, there is a higher residual exposure after th[r] ...
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An Error Correction Analysis of Visitor Arrivals to the Bahamas
... develop forecasting models primarily rely on structural time series models (Greenidge, 2000); univariate and transfer function autoregressive integrated moving average (ARIMA) models; and ...
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Online Full Text
... price forecasting. The efficiency of the developed GWO forecasting models is measured based on Mean Absolute Percentage Error and prediction accuracy and is compared against the ones produced by ...
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Moving Averege Models in Forecasting Methods
... basic forecasting models such as Naive, Moving averages, Simple smoothing, Double moving averages and Double smoothing, triple smoothing and adaptive smoothing forecasting ...
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Forecasting Macedonian GDP: Evaluation of different models for short term forecasting
... series models are the unobserved components (UC) models ...these models, an observable economic series can be expressed as consisting of unobservable ...series models (for instance, random ...
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Exact Likelihood Estimation and Probabilistic Forecasting in Higher order INAR(p) Models
... We have solved the open problem that in INAR(p) models, both the likelihood function and multi-step probabilistic forecasts “seem” to be computationally intractable. Our method is based on i) the simple ...
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Short-Term Forecast of Wind Speed through Mathematical Models
... models for forecasting time series applied in wind generation based on the combination of time series 828. models with artificial neural networks[r] ...
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An Autoregressive Integrated Moving Average Models For Process Output And Forecasting
... This is the use of data and any information on how the series was generated, to suggest a subclass of parsimonious models worthy to be entertained. In achieving this time plot autocorrelation function, ...
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In-sample forecasting: structured models and reserving
... For example when reserves for outstanding liabilities are to be estimated in insurance companies, there is usually no follow-up data of individuals in the portfolio available and reported claims, categorized in different ...
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A ranking of VAR and structural models in forecasting
... candidate models and run information criteria to select the best ...candidate models for constructed annual and quarterly ARIMA. All the models have in common an integrated component of first order; ...
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Forecasting telecommunications data with linear models
... Note: RT is the robust trend model; ARIMA is the autoregressive integrated moving average model; HOLT is Holt’s linear no trend model; Holt-D is Holt’s model with exponential smoothing; [r] ...
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Multivariate Forecasting with BVARs and DSGE Models
... DSGE models the most important finding is that their predictive scores are higher than their relative multivariate point forecast accuracy ...these models are helpful in producing a plausible covariance ...
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Theory of economic models for forecasting and policy
... 14 management and innovation are also required in firms, institutions and households* The super-ego function is likewise exercised in all of the individuals, households, firms and instit[r] ...
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Forecasting by (Arima) models Toinflation rate in Sudan
... Inflation is an economic phenomenon that have attracted the attention of many economists and researchers. There is a wide variety of opinions among researchers on the causes of inflation and how it could be reduced. In ...
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