AN ADAPTIVE APPROACH TO TIME‐SERIES FORECASTING

Stuart I. Bretschneider · R. L. Longini

36 citations0/0 files storedDecision Sciences

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 This paper extends the applicability of the Carbone‐Longini adaptive estimation procedure (AEP) to time‐series forecasting. Comparisons with adaptive filtering, the Box‐Jenkins methodology, and multiple regression analysis as it applies to time‐series analysis are provided. Specific time‐series data examined by Box and Jenkins and Box and Tiao constitute the basis for these comparisons. The analysis of the results indicate the robustness and performance superiority of the simple distributive‐lag forecast model coupled with the concept of adaptively “tracking” rather than “fitting” historical data.

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 — 36 citations exist upstream.

References

1977Time Series Analysis: Forecasting and Control 1977Adaptive Filtering: An Integrated Autoregressive/Moving Average Filter for Time Series Forecasting

Cited by

1989Forecasting with combined seasonal indices 1992A comparison of time series and econometric models for forecasting restaurant sales 1994A Two-Stage Sales Forecasting Procedure Using Discounted Least Squares

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.