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When the anomaly detection model was used, the records were divided into two peer groups, with an anomaly index cutoff of 1.760.
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Different basic models, such as extreme value analysis, probabilistic and statistical models, linear models, proximity-based models, information theoretical models, high dimensional outlier detection models, are used for detection of outliers in the data.
A relative detection efficiency model was used to correct the lightning data.
To calculate calamity detection capability, an atmospheric dispersion model was used to simulate potentially harmful radioactive releases.
A random effects model was used for detection of substantial heterogeneity (P = 0.08, I = 61 %).
To assess whether the effect of time interval to BC2 or mode of detection differed with age, a Cox model was used with a term for interaction between each of these factors and age.
To test whether exon length and abundance, and the interaction between them contribute to differences in detection among technical replicates a logistic regression model was used.
The model was used as the emission probability of the null state of a hidden Markov model for peak detection.
Finally, the fusion model is used for vehicle detection.
When the model is used for prospective detection of epidemics, it is often safer to use only a linear trend to avoid inconsistencies when the model will be extrapolated into the future.
A Poisson model is used for maximum likelihood detection in optical communications [10].
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