testingObsModel: Case Ascertainment observational model for a discrete-time...
In JMacDonaldPhD/REpi: Pseudo-Marginal Analysis of partially observed Epidemics
testingObsModel R Documentation
Case Ascertainment observational model for a discrete-time meta-population SIR model.
Description
Generates a testing observation model. There is assumed
to be a fixed probability \alpha of an individual being recruited for testing, independent
of time and individual. There is then an associated sensitivity and specificity for the test.
Usage
testingObsModel(epidemic)
Arguments
epidemic
Underlying epidemic trajectory
Value
Returns a sampling function and a log-density calculation function.
JMacDonaldPhD/REpi documentation built on Aug. 2, 2022, 2:09 p.m.
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| testingObsModel | R Documentation |
Case Ascertainment observational model for a discrete-time meta-population SIR model.
Description
Generates a testing observation model. There is assumed to be a fixed probability \alpha of an individual being recruited for testing, independent of time and individual. There is then an associated sensitivity and specificity for the test.
Usage
testingObsModel(epidemic)
Arguments
epidemic |
Underlying epidemic trajectory |
Value
Returns a sampling function and a log-density calculation function.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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