Results 261 to 270 of about 105,549 (303)

ARIMA modelling of birth data

Journal of Applied Statistics, 1989
In this article the fitting of ARIMA models to time series relating to the births at Edendale Hospital in Natal, South Africa, over a 16-year period is discussed. The model (011)X(011)12 provides andexcellent fit to the monthly totals of mothers delivered but serious discrepancies between estimates of the moving average parameters obtained by the ...
L. M. Haines, W. P. Munoz, C. J. Van Gelderen   +2 more
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ARMA- und ARIMA-Modelle

1990
Kann eine vorliegende Zeitreihe x1, x2,…,xT, als Realisation eines schwach stationaren stochastischen Prozesses angesehen werden, dann ist es entweder ein AR(p)-Prozess, ein MA(q)-Prozess oder eine Mischung aus einem schwach stationaren autoregressiven Prozess Xt p-ter Ordnung des (mittelwertbereinigten) Outputs mit einem gleitenden ...
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In defense of ARIMA modeling

International Journal of Forecasting, 1990
Abstract A number of empirical studies published in the forecasting literature in the 1970's and 1980's have come to the conclusion that univariate ARIMA time series modeling (Box-Jenkins) is not a more accurate univariate time series forecasting method than some simpler and older alternatives, including various exponential smoothing methods.
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ARIMA- und SARIMA-Modelle

2014
Bisher wurden in diesem Kapitel die linearen Modelle dazu benutzt, ausschlieslich stationare Prozesse zu modellieren und prognostizieren.
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Robust estimation of ARIMA models

Journal of Econometrics, 1981
Abstract The paper discusses methods of estimating univariate ARIMA models with outliers. The approach calls for a state vector representation of a time-series model, on which we can then operate on using the Kalman filter. One of the additional advantages of Kalman filter operating on the state vector representation is that the method and code could
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An ARIMA Supply Chain Model

Management Science, 2005
This paper presents a multistage supply chain model that is based on Autoregressive Integrated Moving Average (ARIMA) time-series models. Given an ARIMA model of consumer demand and the lead times at each stage, it is shown that the orders and inventories at each stage are also ARIMA, and closed-form expressions for these models are given.
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ARIMA Models and Signal Extraction

2001
Back to the Wold representation (2.18) of a stationary process, z t = Ψ(B)a t , the representation is of no help from the point of view of fitting a model because, in general, the polynomial Ψ(B) will contain an infinite number of parameters. Therefore we use a rational approximation of the type $$ \Psi \left( B \right) \doteq \frac{{\theta \left ...
Regina Kaiser, Agustín Maravall
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ARIMA and Seasonal Models

2022
Wayne A. Woodward, Bivin P. Sadler, Stephen D. Robertson   +2 more
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Economic Forecasting using ARIMA Modelling

2018
The Box-Jenkins approach to time series modelling consists of extracting predictable movements (or patterns) from the observed data through a series of iterations. The univariate Box-Jenkins method is purely a forecasting tool; no explanation is offered in that there are no regressor-type variables.
Abdulkader Aljandali, Motasam Tatahi
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ARIMA Modeling and Forecasting

2023
Patrick Woitschig, Wolfgang Karl Härdle
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