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Confidence bands and intervals are valuable tools in evaluating how good a model fits data. Here's some reading for the technical/mathematical implementation. In addition, we need to think about the API. I suggest adding a method to either FitResults, or to Model.
Confidence bands and intervals are valuable tools in evaluating how good a model fits data. Here's some reading for the technical/mathematical implementation. In addition, we need to think about the API. I suggest adding a method to either
FitResults
, or toModel
.https://www.graphpad.com/support/faq/how-does-prism-compute-confidence-and-prediction-bands-for-nonlinear-regression/
https://stats.stackexchange.com/questions/85448/shape-of-confidence-and-prediction-intervals-for-nonlinear-regression
https://stats.stackexchange.com/questions/15423/how-to-compute-prediction-bands-for-non-linear-regression
References in https://www.mathworks.com/help/stats/nlpredci.html
https://stat.ethz.ch/~stahel/courses/cheming/nlreg10E.pdf
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