1988Journal of Applied StatisticsRequires access

What is the ‘best’ method of forecasting?

Chris Chatfield

Open publisher page 101 citations

Abstract

Forecasting methods are reviewed. They may be classified into univariate, multivariate and judgemental methods, and also by whether an automatic or non-automatic approach is adopted. The choice of ‘best’ method depends on a wide variety of considerations. The use of forecasting competitions to compare the accuracy of univariate methods is discussed. The strengths and weaknesses of different univariate methods are compared, both in automatic and non-automatic mode. Some general recommendations are made as well as some suggestions for future research.

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What this paper is about

Forecasting methods are reviewed. They may be classified into univariate, multivariate and judgemental methods, and also by whether an automatic or non-automatic approach is adopted. The choice of ‘best’ method depends on a wide variety of considerations. The use of forecasting competitions to compare the accuracy of univariate methods is discussed. The strengths and weaknesses of different univariate methods are compared, both in automatic and non-automatic mode. Some general recommendations are made as well as some suggestions for future research.

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OpenAlex reports 101 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Forecasting methods are reviewed. They may be classified into univariate, multivariate and judgemental methods, and also by whether an automatic or non-automatic approach is adopted. The choice of ‘best’ method depends on a wide variety of considerations. The use of forecasting competitions to compare the accuracy of univariate methods is discussed. The strengths and weaknesses of different univariate methods are compared, both in automatic and non-automatic mode. Some general recommendations are made as well as some suggestions for future research.

Key concepts: Univariate, Strengths and weaknesses, Computer science, Multivariate statistics, Variety (cybernetics), Data mining, Econometrics, Statistics

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