Event Model for Gaussian Dates
Usage
eventModel_Gauss(
M,
s,
studyPeriodMin,
studyPeriodMax,
refYear = NULL,
numberChains = 2,
numberAdapt = 10000,
numberUpdate = 10000,
variable.names = c("theta"),
numberSample = 50000,
thin = 10
)Arguments
- M
A [`numeric`] vector of measurements.
- s
A [`numeric`] vector of errors.
- studyPeriodMin
A length-one [`numeric`] vector specifying the start time of the study period.
- studyPeriodMax
A length-one [`numeric`] vector specifying the end time of the study period.
- refYear
A [`numeric`] vector specifying the reference year. If `NULL` (the default), AD years are expected.
- numberChains
An [`integer`] giving the number of of parallel chains for the model (see [rjags::jags.model()]).
- numberAdapt
An [`integer`] giving the number of iterations for adaptation (see [rjags::jags.model()]).
- numberUpdate
An [`integer`] giving the number of iterations to update the model by.
- variable.names
A [`character`] vector giving the names of variables to be monitored (see [rjags::coda.samples()]).
- numberSample
An [`integer`] giving the number of iterations to monitor (see [rjags::coda.samples()]).
- thin
An [`integer`] giving the thinning interval for monitors (see [rjags::coda.samples()]).