[Pomp-commits] r1010 - pkg/pomp/man

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Tue Sep 23 21:23:08 CEST 2014


Author: kingaa
Date: 2014-09-23 21:23:08 +0200 (Tue, 23 Sep 2014)
New Revision: 1010

Modified:
   pkg/pomp/man/bsmc.Rd
Log:
- merge bsmc2.Rd with bsmc.Rd

Modified: pkg/pomp/man/bsmc.Rd
===================================================================
--- pkg/pomp/man/bsmc.Rd	2014-09-23 19:23:03 UTC (rev 1009)
+++ pkg/pomp/man/bsmc.Rd	2014-09-23 19:23:08 UTC (rev 1010)
@@ -1,17 +1,27 @@
-\name{bsmc}
+\name{bsmc2}
+\title{Liu and West Bayesian Particle Filter}
 \alias{bsmc}
 \alias{bsmc-pomp}
 \alias{bsmc,pomp-method}
-\title{Liu and West Bayesian Particle Filter}
+\alias{bsmc2}
+\alias{bsmc2-pomp}
+\alias{bsmc2,pomp-method}
+\alias{$,bsmcd.pomp-method}
+\alias{$-bsmcd.pomp}
+\alias{plot,bsmcd.pomp-method}
+\alias{plot-bsmcd.pomp}
 \description{
-  Generates draws from the posterior distribution for the parameters using the Liu and West algorithm.
-  \code{bsmc} gives draws from the posterior.
+  Modified versions of the Liu and West (2001) algorithm.
 }
 \usage{
 \S4method{bsmc}{pomp}(object, params, Np, est, smooth = 0.1,
      ntries = 1, tol = 1e-17, lower = -Inf, upper = Inf, seed = NULL,
      verbose = getOption("verbose"), max.fail = 0,
      transform = FALSE, \dots)
+\S4method{bsmc2}{pomp}(object, params, Np, est, smooth = 0.1,
+     tol = 1e-17, seed = NULL,
+     verbose = getOption("verbose"), max.fail = 0,
+     transform = FALSE, \dots)
 }
 \arguments{
 \item{object}{
@@ -103,11 +113,15 @@
   There are two ways to specify the prior distribution of particles.
   If \code{params} is unspecified or is a named vector, \code{Np} draws are made from the prior distribution, as specified by \code{\link{rprior}}.
   Alternatively, \code{params} can be specified as an \code{npars} x \code{Np} matrix (with rownames).
+
+  \code{bsmc} uses version of the original algorithm that includes a plug-and-play auxiliary particle filter.
+  \code{bsmc2} discards this auxiliary particle filter and appears to give superior performance for the same amount of effort.
 }
 \author{
   Michael Lavine (lavine at math dot umass dot edu),
   Matthew Ferrari (mferrari at psu dot edu),
   Aaron A. King
+  Edward L. Ionides
 }
 \references{
   Liu, J. and M. West.



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