Principles of forecasting : a handbook for researchers and practitioners

By J. Armstrong, George T. Duncan, Wilpen L. Gorr. 2001

455 citations recorded by the source corpus.

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Citations in the corpus

Predictive Analytics in Information Systems Research (2011, unknown): “Predictive power is compared against naive and alternative predictive models (see Armstrong 2001).”
Combination of long term and short term forecasts, with application to tourism demand forecasting (2011, unknown): “One favorable feature to have in a forecast combination system is diversity in the underlying forecasting models, as a safeguard against focusing over much on a narrow specification (see Armstrong, 2001).”
Performance of Combined Double Seasonal Univariate Time Series Models for Forecasting Water Demand (2009, unknown): “Combining forecasts can reduce errors by averaging of individual forecasts (Clemen, 1989, Armstrong 2001) and is particularly useful when we are uncertain about which forecasting method is better for future prediction.”
Forecast combinations of computational intelligence and linear models for the NN5 time series forecasting competition (2011, unknown): “Armstrong (2001) advocates generally using five or six models.”
Cost Overruns in Large-scale Transportation Infrastructure Projects: Explanations and Their Theoretical Embeddedness (2010, unknown): “Narrow focus Wachs (1987, 1989) Morris (1990) Arvan and Leite (1990) Kahneman (1993, 2003) Knudsen (1976) Fouracre et al. (1990) Pickrell (1992) Auditor General of Sweden (1994) Mansfield et al.”
Forecasting Decisions in Conflict Situations: A Comparison of Game Theory, Role-playing, and Unaided Judgement (2002, unknown): “This the eight groups with 'natural leaders' and finding is consistent with Armstrong (2001a), 'quantitative analysis experts' allocated to roles who reported 13 percent correct for the same was similar to that of the other nine groups— situations. there were five correct forecasts from each…”
Simple versus complex forecasting: The evidence (2015, unknown): “The Tree is the product of 40 leading experts in various areas of forecasting from different disciplines, and 123 reviewers (Armstrong 2001), along with evidence cited on the forecastingprinciples.com site since 2001.”
To combine or not to combine: selecting among forecasts and their combinations (2005, unknown): “However this is ‘‘equally unfair’’ for both individual methods and their combinations, although there are indications that combinations are advantageous for long-term forecasting (Armstrong, 2001).”
An experimental investigation of kernels on graphs for collaborative recommendation and semisupervised classification (2012, unknown): “The idea originates (see the survey in Adomavicius & Tuzhilin, 2005) mainly from research on machine learning, information retrieval (Salton, 1989), cognitive science (Rich, 1979), forecasting theories (Armstrong, 2001), marketing (Lilien, Smith, & Moorthy, 1992), and management (Murthi & Sarkar, 20”
Forecasting across time series databases using recurrent neural networks on groups of similar series: A clustering approach (2017, background): “This includes lack of empirical evidence and absence of evaluation metrics and standard benchmarks that are widely accepted in the forecasting community (Armstrong, 2006; Scott Armstrong, 2001).”
A new accuracy measure based on bounded relative error for time series forecasting (2017, background): “However, RMSE is also sensitive to forecasting outliers [28].”
Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences (2006, unknown): “…the tendency of judges to discount advice, and the benefits to judges’ decision accuracy from combining multiple sources of advice— were anticipated by findings in the literatures on forecasting and decision aids (see Clemen, 1989; Collopy, Adya, & Armstrong, 2001; Harvey, 2001; Stewart, 2001).”