Selected article for: "partial prcc rank correlation coefficient and prcc rank correlation coefficient"

Author: Miles D. Miller-Dickson; Victor A. Meszaros; Francis Baffour-Awuah; Salvador Almagro-Moreno; C. Brandon Ogbunugafor
Title: Waterborne, abiotic and other indirectly transmitted (W.A.I.T.) infections are defined by the dynamics of free-living pathogens and environmental reservoirs
  • Document date: 2019_1_20
  • ID: d9mxtc8d_60
    Snippet: Having demonstrated the structural relevance of the WAIT framework in terms of how it influences the basic reproductive number, we can consider the utility of the model with respect to other properties, including how it offers insight into potential interventions. Fig. 5 : R 0 sensitivity in HCV: the Partial Rank Correlation Coefficient (PRCC). A PRCC calculation was performed for R 0 using Latin Hypercube Sampling. Parameters were sampled from u.....
    Document: Having demonstrated the structural relevance of the WAIT framework in terms of how it influences the basic reproductive number, we can consider the utility of the model with respect to other properties, including how it offers insight into potential interventions. Fig. 5 : R 0 sensitivity in HCV: the Partial Rank Correlation Coefficient (PRCC). A PRCC calculation was performed for R 0 using Latin Hypercube Sampling. Parameters were sampled from uniform distributions with widths specified by the ranges given in Table II . The PRCC calculation was repeated for 50 independent iterations. The average of these iterations is shown here, with the standard deviations for each parameter shown as the error bars.

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