Local Regression Models

By William S. Cleveland, E. Grosse, William M. Shyu. 2017

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Using Genetic Distance to Infer the Accuracy of Genomic Prediction (2015, methodology): “Estimate the decay curve from the sets of (F̂ (m) ST , ρ̂ (m) D ) points using local regression (LOESS; [10]), which can be used to produce both the mean and its 95% confidence interval at any point in the range of observed F̂ST.”
Exploring the sources of uncertainty: Why does bagging for time series forecasting work? (2018, methodology): “For non-seasonal time series (i.e., frequency = 1), a loess-based procedure (Cleveland et al., 1992) is employed to obtain a decomposition into trend and remainder, without a seasonal component.”
Association of brain amyloidosis with pro-inflammatory gut bacterial taxa and peripheral inflammation markers in cognitively impaired elderly. (2017, methodology): “For the evaluation of correlations between stool bacteria and blood inflammation biomarkers, the algorithm for smoothing scatterplots by robust locally weighted regression (Cleveland et al., 1992) was applied to draw the fitted curves.”