Exhaustive Goodness of Fit Via Smoothed Inference and Graphics

@article{Algeri2020ExhaustiveGO,
  title={Exhaustive Goodness of Fit Via Smoothed Inference and Graphics},
  author={Sara Algeri and X. Zhang},
  journal={Journal of Computational and Graphical Statistics},
  year={2020},
  volume={31},
  pages={378 - 389}
}
  • S. AlgeriX. Zhang
  • Published 26 May 2020
  • Computer Science
  • Journal of Computational and Graphical Statistics
Abstract Classical tests of goodness of fit aim to validate the conformity of a postulated model to the data under study. Given their inferential nature, they can be considered a crucial step in confirmatory data analysis. In their standard formulation, however, they do not allow exploring how the hypothesized model deviates from the truth nor do they provide any insight into how the rejected model could be improved to better fit the data. The main goal of this work is to establish a… 
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