kurtis-s / overture

# Compare  70c5215 ... +0 ... 8787cdd 

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@@ -33,14 +33,14 @@
 33 33 34 34 #' Turn a non-adaptive Metropolis sampler into an adaptive Metropolis sampler 35 35 #' 36 - #' Given a non-adpative sampler of the form f(..., s), \code{Amwg} will return a 36 + #' Given a non-adaptive sampler of the form f(..., s), \code{Amwg} will return a 37 37 #' function g(...) that automatically adapts the Metropolis proposal standard 38 - #' deviation s to try and acheive a target acceptance rate. 38 + #' deviation s to try and achieve a target acceptance rate. 39 39 #' 40 40 #' \code{Amwg} uses the Adaptive Metropolis-Within-Gibbs algorithm from Roberts 41 41 #' & Rosenthal (2009), which re-scales the proposal standard deviation after a 42 42 #' fixed number of MCMC iterations have elapsed. The goal of the algorithm is 43 - #' to acheive a target acceptance rate for the Metropolis step. After the 43 + #' to achieve a target acceptance rate for the Metropolis step. After the 44 44 #' n\emph{th} batch of MCMC iterations the log of the proposal standard 45 45 #' deviation, \eqn{log(s)}, is increased/decreased by \eqn{\delta(n)}. 46 46 #' \eqn{log(s)} is increased by \eqn{\delta(n)} if the observed acceptance rate
@@ -71,7 +71,7 @@
 71 71 #' by \eqn{f}. This functionality can be used, for example, if \eqn{f} samples 72 72 #' each of its returned elements individually, updating each element using a 73 73 #' Metropolis step. See the examples for an illustration of this use case. In 74 - #' such settings, \eqn{f} should be contructed to receive \eqn{s} as a vector 74 + #' such settings, \eqn{f} should be constructed to receive \eqn{s} as a vector 75 75 #' argument. 76 76 #' 77 77 #' @param f non-adaptive Metropolis sampler of the form f(..., s)

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