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- W2913541211 abstract "The research on commuting has emerged in recent decades, but the issue of whether the empirical techniques used are appropriate has not been analysed. Thus, results from prior research could be based on non-accurate models, leading to misleading conclusions. We apply an algorithmic approach based on bootstrapping, variable selection, and mean absolute prediction errors, which is designed to avoid overfitting. Using the American Time Use Survey, we find that models with a reduced set of explanatory variables have similar accuracy to standard econometric models. Our results shed light on the importance of determining whether models can be overfitted." @default.
- W2913541211 created "2019-02-21" @default.
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- W2913541211 date "2019-02-08" @default.
- W2913541211 modified "2023-10-04" @default.
- W2913541211 title "Modelling commuting time in the US: Bootstrapping techniques to avoid overfitting" @default.
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- W2913541211 doi "https://doi.org/10.1111/pirs.12424" @default.
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