Selected article for: "confidence interval and statistical significance"

Author: Neri, Franco M.; Cook, Alex R.; Gibson, Gavin J.; Gottwald, Tim R.; Gilligan, Christopher A.
Title: Bayesian Analysis for Inference of an Emerging Epidemic: Citrus Canker in Urban Landscapes
  • Document date: 2014_4_24
  • ID: 01yc7lzk_40
    Snippet: The non-parametric estimator used here for C T (d) is the spline correlogram [45] . A 95% confidence interval for the estimated experimental autocorrelation function was calculated from 1000 bootstrapped datasets, generated from the experimental data, using a dedicated algorithm [45] . Finally, the statistical significance of autocorrelation functions was evaluated by generating 1000 simulated datasets where the infection status of each host was .....
    Document: The non-parametric estimator used here for C T (d) is the spline correlogram [45] . A 95% confidence interval for the estimated experimental autocorrelation function was calculated from 1000 bootstrapped datasets, generated from the experimental data, using a dedicated algorithm [45] . Finally, the statistical significance of autocorrelation functions was evaluated by generating 1000 simulated datasets where the infection status of each host was re-allocated randomly (see e.g. [46] ). We refer the reader to Text S1 for a brief introduction to spline correlogram calculation and related techniques.

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