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The first approach, when the effect of the influenza parameter is estimated, uses influenza data as an indicator variable, which most likely underestimates the impact of influenza during the winter season.
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Parameters were estimated using maximum-likelihood estimation.
Correlations were estimated using a robust bicorrelation mid-weight estimator.
Transcript abundance was estimated using TPM.
CTF parameters were estimated using CTFFIND435.
Turnover rates of orthogroups were estimated using the ML fitting.
The effect size was estimated using Cohen's d47.
Subjective values were estimated using the RL model (Methods).
Immigration and emigration are both estimated using a survey (International Passenger Survey).
The membrane position was estimated using the PPM server49.
Single subject effects were estimated using a fixed-effect model.
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