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We also quantify the effect of inaccuracies in sensing. We demonstrate improved performance by estimating τ for every individual, both with artificially created and human subject data. Prediction accuracy improves with every newly available observation. The estimated τ -s correlate well with the subjects' chronotypes, in a similar way as τ correlates. Our results show that individualizing the estimation of model parameters can improve circadian state estimation accuracy. These findings underscore the potential improvements in personalized
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