Selected article for: "relative standard deviation and standard deviation"

Author: Alessio Notari
Title: Temperature dependence of COVID-19 transmission
  • Document date: 2020_3_30
  • ID: 0oma7hdu_13
    Snippet: In addition, a decreasing trend is also visible in this dataset, below about 10 • C. For this reason we also fit with a quadratic function α(T ) = α 0 − β(T − T M ) 2 . Results for the quadratic best fit are presented in fig. 3 . The relative estimate, standard deviation and confidence intervals for the parameters are shown in Table II . From such results a peak is visible at around T M ≈ 8 • C. The quadratic model is able to explain.....
    Document: In addition, a decreasing trend is also visible in this dataset, below about 10 • C. For this reason we also fit with a quadratic function α(T ) = α 0 − β(T − T M ) 2 . Results for the quadratic best fit are presented in fig. 3 . The relative estimate, standard deviation and confidence intervals for the parameters are shown in Table II . From such results a peak is visible at around T M ≈ 8 • C. The quadratic model is able to explain a slightly larger part of the variance of the data, since R 2 ≈ 0.27 [13] . Moreover, despite the presence of an extra parameter, one may quantify the improvement of the fit, using for instance the Akaike Information Criterion (AIC) for model comparison, ∆AIC ≡ 2∆k − 2∆ ln(L), where ∆k is the increase in the number of parameters, compared to the simple linear model, and ∆ ln(L) is the change in the maximum log-likelihood between the two models. This gives ∆AIC = −2.1, slightly in favor of the quadratic model. . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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