A unified view of statistical forecasting procedures

Andrew C. Harvey

238 citations0/0 files storedJournal of Forecasting

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Forecasting Techniques and Applications Time Series Analysis and Forecasting Statistical and numerical algorithms

Abstract

Abstract A large number of statistical forecasting procedures for univariate time series have been proposed in the literature. These range from simple methods, such as the exponentially weighted moving average, to more complex procedures such as Box–Jenkins ARIMA modelling and Harrison–Stevens Bayesian forecasting. This paper sets out to show the relationship between these various procedures by adopting a framework in which a time series model is viewed in terms of trend, seasonal and irregular components. The framework is then extended to cover models with explanatory variables. From the technical point of view the Kalman filter plays an important role in allowing an integrated treatment of these topics.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 238 citations exist upstream.

References

1977Time Series Analysis: Forecasting and Control 2000Forecasting Economic Time Series 1982The accuracy of extrapolation (time series) methods: Results of a forecasting competition 1967Applied Economic Forecasting 1965The Distributed Lag Between Capital Appropriations and Expenditures 1983The Econometric Analysis of Time Series.1977Forecasting Economic Time Series 1976Bayesian Forecasting

Cited by

1987Structural change and the combination of forecasts 1992Vancouver's Gasoline-Price Wars: An Empirical Exercise in Uncovering Supergame Strategies 2000Estimating the Underlying Change in Unemployment in the UK 1986Stochastic Trends in Dynamic Regression Models: An Application to the Employment-Output Equation 1990Recursive estimation and forecasting of non‐stationary time series 1988What is the ‘best’ method of forecasting?

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.