## [404779]: man / adapt.Rd  Maximize  Restore  History

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  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 \name{adapt} \alias{adapt} \title{Adaptive phase for JAGS models} \description{ Update the model in adaptive mode. } \usage{ adapt(object, n.iter, end.adaptation=TRUE, \dots) } \arguments{ \item{object}{a \code{jags} model object} \item{n.iter}{length of the adaptive phase} \item{end.adaptation}{logical flag. If \code{TRUE} then adaptive mode will be automatically on exit. \item{\ldots}{additional arguments to the update method} } \value{ Returns \code{TRUE} if all the samplers in the model have successfully adapted their behaviour to optimum performance and \code{FALSE} otherwise. } \details{ This function is not normally called by the user. It is called by the \code{jags.model} function when the model object is created. When a JAGS model is compiled, it may require an initial sampling phase during which the samplers adapt their behaviour to maximize their efficiency (e.g. a Metropolis-Hastings random walk algorithm may change its step size). The sequence of samples generated during this adaptive phase is not a Markov chain, and therefore may not be used for posterior inference on the model. The \code{adapt} function updates the model for \code{n.iter} iterations in adaptive mode. Then each sampler reports whether it has acheived optimal performance (e.g. whether the rejection rate of a Metropolis-Hasting sampler is close to the theoretical optimum). If any sampler reports failure of this test then \code{adapt} returns \code{FALSE}. By default, the \code{adapt()} function turns off adaptive mode on exit. Further calls to \code{adapt()} do nothing. The model may be maintained in adaptive mode with the option \code{end.adaptation = FALSE} so that successive calls to \code{adapt()} may be made until adaptation is satisfactory. } \author{Martyn Plummer} \keyword{models}