Fast and frugal forecasting

@article{Goldstein2009FastAF,
  title={Fast and frugal forecasting},
  author={Daniel G. Goldstein and Gerd Gigerenzer},
  journal={International Journal of Forecasting},
  year={2009},
  volume={25},
  pages={760-772}
}

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References

SHOWING 1-10 OF 65 REFERENCES
The accuracy of extrapolation (time series) methods: Results of a forecasting competition
TLDR
The results of a forecasting competition are presented to provide empirical evidence about differences found to exist among the various extrapolative (time series) methods used in the competition.
Models of ecological rationality: the recognition heuristic.
TLDR
The recognition heuristic, arguably the most frugal of all heuristics, makes inferences from patterns of missing knowledge that leads to the counterintuitive less-is-more effect in which less knowledge is better than more for making accurate inferences.
Accuracy of Forecasting: An Empirical Investigation
In this study, the authors used 111 time series to examine the accuracy of various forecasting methods, particularly time-series methods. The study shows, at least for time series, whysome methods
Simple heuristics and rules of thumb: Where psychologists and behavioural biologists might meet
Fast and frugal heuristics in sports.
The M2-competition: A real-time judgmentally based forecasting study
Fast, frugal, and fit: Simple heuristics for paired comparison
TLDR
An overview of recent results on lexicographic, linear, and Bayesian models for paired comparison from a cognitive psychology perspective, and identifies the optimal model in each class, where optimality is defined with respect to performance when fitting known data.
“Take-the-Best” and Other Simple Strategies: Why and When they Work “Well” with Binary Cues
The effectiveness of decision rules depends on characteristics of both rules and environments. A theoretical analysis of environments specifies the relative predictive accuracies of the
The robust beauty of improper linear models in decision making.
Proper linear models are those in which predictor variables are given weights in such a way that the resulting linear composite optimally predicts some criterion of interest; examples of proper
Geographic Profiling: The Fast, Frugal, and Accurate Way
The current article addresses the ongoing debate about whether individuals can perform as well as actuarial techniques when confronted with real world, consequential decisions. A single experiment
...
...