Time Series Modelling
Time series modelling to forecast prehospital EMS demand for diabetic emergencies
... of time series modelling in health care to pre- dict future events is ...of time series prediction modelling, the ARIMA/SARIMA method has some distinct ...ARIMA modelling ...
9
Time series modelling and forecasting of Sarawak black pepper price
... up time series modelling and forecasting of the Sarawak black pepper ...(ARMA) time series models fit the price series well and they have correctly predicted the future trend of ...
17
Aspects of macroeconometric time series modelling
... E xpectations over a much longer horizon, such as six or twelve months ahead, would be useful in analysing the role lo n g er-ru n expectations play in determ ining economic activ ity in[r] ...
421
Financial Time Series Modelling of Trends and Patterns in the Energy Markets
... a time series path is important to policy makers, statisticians, economists, traders, hedgers and speculators ...correct time series path is also a key ingredient in pricing ...depict ...
14
Time series modelling for forecasting vehicular traffic flow in Dublin
... In this paper three different conventional and non-conventional time-series techniques are used for modeling the traffic flow data in Dublin City. The random walk model, Holt Winters’ exponential smoothing ...
22
Time series modelling of birth data
... birth time series with other variable time series may not significantly improve the result of birth ...birth series forecast their future values may be achieved by comparing birth ...
114
Time series modelling of the Kobe Osaka earthquake recordings
... X(t) series and the covariance structure of the white-noise, any standard procedure of estimation such as the maximum likelihood (ML) can be used to estimate the parameters in the model and the covariance function ...
13
Time series modelling of increased soil temperature anomalies during long period
... A b s t r a c t. Soil temperature just beneath the soil surface is highly dynamic and has a direct impact on plant seed germi- nation and is probably the most distinct and recognisable factor governing emergence. ...
7
Freight-Forward Agreement Time series Modelling Based on Artificial Neural Network Models
... An important advantage offered by ANNs is that they can constantly enrich their knowledge with new information resulting from new market conditions. The decisive factor is the volatility of the market being studied, as ...
6
Structural Time Series Modelling of Capacity Utilisation
... The plan of the paper is the following: the next section will introduce the univariate model, by which capacity is measured using the output series alone. Section 3 presents an application with respect to US ...
30
Concepts and tools for nonlinear time series modelling
... Tweedie, Random Coefficient Autoregressive Processes: a Markov Chain Analysis of Stationarity and Finiteness of Moments, Journal of Time Series Analysis, 6 1985 1–14.. Findley, The overf[r] ...
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Statistical modelling of agrometeorological time series by exponential smoothing
... A time series is an ordered sequence of values of a va- riable at equally spaced time intervals, eg hourly tem- peratures at weather ...of time series modelling is to carefully ...
9
Importance sampling techniques for estimation of diffusions models
... in time-series modelling is due to various reasons: they provide a flexible framework for modelling both stationary processes with quite general invariant distributions and non-stationary ...
27
The Karkheh River Streamflow Forecast based on the Modelling of Time Series
... Autoregressive integrated moving average (ARIMA) models are appropriate for the annual streamflows (annual peak and maximum and also mean discharges) of the Karkheh River at Jelogir Majin station of Karkheh river basin ...
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Modelling multiple time series with missing observations
... T h e aim of this thesis is to deve l op a me t h o d of fit t ing state space mo de l s to mul ti var iat e t i me series data cont ai ni ng missing observations. T h e model is i llust rated by using it to model ...
153
Modelling and Analysis on Noisy Financial Time Series
... historical time series has attracted many researchers in last few dec- ...financial time series. With the filtered time series, the statistical model known as autoregression is ...
6
Estimation of the Semiparametric Factor Model: Application to Modelling Time Series of Electricity Spot Prices
... Estimation of the Semiparametric Factor Model: Application to Modelling Time Series of Electricity Spot Prices.. Liebl, Dominik University of Cologne..[r] ...
7
Stochastic Characteristics and Modelling of Monthly Rainfall Time Series of Ilorin, Nigeria
... the series takes on nonzero and zero values throughout the entire length of the record (Figure ...rainfall series; long-term trend pat- tern is seemingly not ...the time series regime leads to ...
14
Modelling time series of industrial production index
... Aim of this work is modelling index industrial performance. In work will be constructed model on base results from business tendency surveys. Business tendency surveys open opportunity for various hypo- theses ...
6
Sparse modelling and estimation for nonstationary time series and high dimensional data
... of time series procedures, the (weak) stationarity assumption has often been adopted, under which the autocovariance functions are constant over time depending only on the time ...in ...
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