[Pomp-commits] r1134 - pkg www www/content www/help

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Wed Mar 4 16:10:11 CET 2015 

Author: kingaa
Date: 2015-03-04 16:10:11 +0100 (Wed, 04 Mar 2015)
New Revision: 1134

Removed:
   www/help/00Index.html
   www/help/00frame_toc.html
   www/help/LondonYorke.html
   www/help/Makefile
   www/help/R.css
   www/help/abc.html
   www/help/basic-probes.html
   www/help/blowflies.html
   www/help/bsmc.html
   www/help/bsplines.html
   www/help/builder.html
   www/help/csnippet.html
   www/help/dacca.html
   www/help/design.html
   www/help/eulermultinom.html
   www/help/example.html
   www/help/gompertz.html
   www/help/index.html
   www/help/logmeanexp.html
   www/help/lowlevel.html
   www/help/mif.html
   www/help/nlf.html
   www/help/ou2.html
   www/help/parmat.html
   www/help/particles-mif.html
   www/help/pfilter.html
   www/help/plugins.html
   www/help/pmcmc.html
   www/help/pomp-fun.html
   www/help/pomp-methods.html
   www/help/pomp-package.html
   www/help/pomp.html
   www/help/pomp.pdf
   www/help/probe.html
   www/help/proposals.html
   www/help/ricker.html
   www/help/rw2.html
   www/help/sannbox.html
   www/help/simulate-pomp.html
   www/help/sir.html
   www/help/spect.html
   www/help/traj-match.html
Modified:
   pkg/Makefile
   www/content/vignettes.htm
   www/index.php
Log:
Revert "- add html version of manual to package website"

Modified: pkg/Makefile
===================================================================
--- pkg/Makefile	2015-03-04 14:18:49 UTC (rev 1133)
+++ pkg/Makefile	2015-03-04 15:10:11 UTC (rev 1134)
@@ -32,25 +32,22 @@
 %.dist %.manual %.vignettes: export R_QPDF=qpdf
 %.dist %.manual %.vignettes: export R_GSCMD=gs
 %.dist %.manual %.vignettes: export GS_QUALITY=ebook
-%.dist %.manual %.vignettes %.help: export R_HOME=$(shell $(REXE) RHOME)
+%.dist %.manual %.vignettes: export R_HOME=$(shell $(REXE) RHOME)
 %.check %.crancheck: export _R_CHECK_ALL_NON_ISO_C_=TRUE
 %.crancheck: export R_PROFILE_USER=./Rprofile
 %.check %.crancheck: export _R_CHECK_WALL_FORTRAN_=TRUE
 %.check %.xcheck: export POMP_FULL_TESTS=yes
-%.vignettes %.help %.data: export R_LIBS=$(CURDIR)/library
+%.vignettes %.data: export R_LIBS=$(CURDIR)/library
 %.bin %.check %.qcheck %.qqcheck %.xcheck %.crancheck %.upload %.publish %.clean %.install %.win: PKG = $*_$(shell perl -ne 'print $$1 if /Version:\s+(\d+\.\d+-\d+)/;' $*/DESCRIPTION)
 
-pomp.vignettes: pomp.install
+pomp.vignettes: pomp.install pomp.manual
 	(cd ../www/vignettes; make)
+	cp pomp.pdf ../www/vignettes
 	$(RCMD) Rdconv -t html pomp/inst/NEWS.Rd -o ../www/content/NEWS.html
 
 pompExamples.vignettes: pompExamples.install
 	(cd pompExamples/vignettes; make)
 
-pomp.help: pomp.install pomp.manual
-	(cd ../www/help; make)
-	cp pomp.pdf ../www/help
-
 %.data: %.install
 	cd $*/inst/data-R; make
 

Modified: www/content/vignettes.htm
===================================================================
--- www/content/vignettes.htm	2015-03-04 14:18:49 UTC (rev 1133)
+++ www/content/vignettes.htm	2015-03-04 15:10:11 UTC (rev 1134)
@@ -7,7 +7,6 @@
 <td><a target="_blank" href="vignettes/getting_started.R">(R code)</a></td>
 </tr>
 <td><strong>pomp</strong> package manual</td>
-<td><a target="_blank" href="help/pomp-package.html">(HTML)</a></td>
-<td><a target="_blank" href="help/pomp.pdf">(PDF)</a></td>
+<td><a target="_blank" href="vignettes/pomp.pdf">(PDF)</a></td>
 </tr>
 </table>

Deleted: www/help/00Index.html
===================================================================
--- www/help/00Index.html	2015-03-04 14:18:49 UTC (rev 1133)
+++ www/help/00Index.html	2015-03-04 15:10:11 UTC (rev 1134)
@@ -1,810 +0,0 @@
-<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
-<html><head><title>R: Statistical Inference for Partially Observed Markov Processes</title>
-<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-<link rel="stylesheet" type="text/css" href="R.css">
-</head><body>
-<h1> Statistical Inference for Partially Observed Markov Processes
-<img class="toplogo" src="http://stat.ethz.ch/R-manual/R-devel/doc/html/logo.jpg" alt="[R logo]">
-</h1>
-<hr>
-<div align="center">
-<a href="http://stat.ethz.ch/R-manual/R-devel/doc/html/packages.html"><img src="http://stat.ethz.ch/R-manual/R-devel/doc/html/left.jpg" alt="[Up]" width="30" height="30" border="0"></a>
-<a href="http://stat.ethz.ch/R-manual/R-devel/doc/html/index.html"><img src="http://stat.ethz.ch/R-manual/R-devel/doc/html/up.jpg" alt="[Top]" width="30" height="30" border="0"></a>
-</div><h2>Documentation for package ‘pomp’ version 0.62-5</h2>
-
-<ul><li><a href="../DESCRIPTION">DESCRIPTION file</a>.</li>
-<li><a href="../doc/index.html">User guides, package vignettes and other documentation.</a></li>
-<li><a href="../demo">Code demos</a>.  Use <a href="../../utils/help/demo">demo()</a> to run them.</li>
-<li><a href="../NEWS">Package NEWS</a>.</li>
-</ul>
-
-<h2>Help Pages</h2>
-
-
-<p align="center">
-<a href="# "> </a>
-<a href="#A">A</a>
-<a href="#B">B</a>
-<a href="#C">C</a>
-<a href="#D">D</a>
-<a href="#E">E</a>
-<a href="#F">F</a>
-<a href="#G">G</a>
-<a href="#I">I</a>
-<a href="#L">L</a>
-<a href="#M">M</a>
-<a href="#N">N</a>
-<a href="#O">O</a>
-<a href="#P">P</a>
-<a href="#R">R</a>
-<a href="#S">S</a>
-<a href="#T">T</a>
-<a href="#V">V</a>
-<a href="#W">W</a>
-<a href="#misc">misc</a>
-</p>
-
-<table width="100%">
-<tr><td width="25%"><a href="pomp-package.html">pomp-package</a></td>
-<td>Inference for partially observed Markov processes</td></tr>
-</table>
-
-<h2><a name="A">-- A --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="abc.html">ABC</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="abc.html">abc</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="abc.html">abc-abc</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="abc.html">abc-class</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="abc.html">abc-method</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="abc.html">abc-methods</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="abc.html">abc-pomp</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="abc.html">abc-probed.pomp</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="abc.html">abcList-class</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="pomp.html">accumulator variables</a></td>
-<td>Constructor of the basic POMP object</td></tr>
-<tr><td width="25%"><a href="pfilter.html">as-method</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">as-method</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="probe.html">as-method</a></td>
-<td>Probe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.</td></tr>
-<tr><td width="25%"><a href="pfilter.html">as.data.frame.pfilterd.pomp</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">as.data.frame.pomp</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-</table>
-
-<h2><a name="B">-- B --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="basic-probes.html">basic.probes</a></td>
-<td>Some useful probes for partially-observed Markov processes</td></tr>
-<tr><td width="25%"><a href="bsmc.html">Bayesian sequential Monte Carlo</a></td>
-<td>The Liu and West Bayesian particle filter</td></tr>
-<tr><td width="25%"><a href="sir.html">bbs</a></td>
-<td>Compartmental epidemiological models</td></tr>
-<tr><td width="25%"><a href="blowflies.html">blowflies</a></td>
-<td>Model for Nicholson's blowflies.</td></tr>
-<tr><td width="25%"><a href="blowflies.html">blowflies1</a></td>
-<td>Model for Nicholson's blowflies.</td></tr>
-<tr><td width="25%"><a href="blowflies.html">blowflies2</a></td>
-<td>Model for Nicholson's blowflies.</td></tr>
-<tr><td width="25%"><a href="bsmc.html">bsmc</a></td>
-<td>The Liu and West Bayesian particle filter</td></tr>
-<tr><td width="25%"><a href="bsmc.html">bsmc-method</a></td>
-<td>The Liu and West Bayesian particle filter</td></tr>
-<tr><td width="25%"><a href="bsmc.html">bsmc-pomp</a></td>
-<td>The Liu and West Bayesian particle filter</td></tr>
-<tr><td width="25%"><a href="bsmc.html">bsmc2</a></td>
-<td>The Liu and West Bayesian particle filter</td></tr>
-<tr><td width="25%"><a href="bsmc.html">bsmc2-method</a></td>
-<td>The Liu and West Bayesian particle filter</td></tr>
-<tr><td width="25%"><a href="bsmc.html">bsmc2-pomp</a></td>
-<td>The Liu and West Bayesian particle filter</td></tr>
-<tr><td width="25%"><a href="bsplines.html">bspline.basis</a></td>
-<td>B-spline bases</td></tr>
-</table>
-
-<h2><a name="C">-- C --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="abc.html">c-abc</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="abc.html">c-abcList</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="abc.html">c-method</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="mif.html">c-method</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">c-method</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="mif.html">c-mif</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="mif.html">c-mifList</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">c-pmcmc</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">c-pmcmcList</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">coef-method</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">coef-pomp</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">coef<-</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">coef<--method</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">coef<--pomp</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pfilter.html">coerce-method</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">coerce-method</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="probe.html">coerce-method</a></td>
-<td>Probe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.</td></tr>
-<tr><td width="25%"><a href="mif.html">compare.mif</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="pfilter.html">cond.logLik</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">cond.logLik-method</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">cond.logLik-pfilterd.pomp</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="mif.html">continue</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="abc.html">continue-abc</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="abc.html">continue-method</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="mif.html">continue-method</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">continue-method</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="mif.html">continue-mif</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">continue-pmcmc</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="mif.html">conv.rec</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="abc.html">conv.rec-abc</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="abc.html">conv.rec-abcList</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="abc.html">conv.rec-method</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="mif.html">conv.rec-method</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">conv.rec-method</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="mif.html">conv.rec-mif</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="mif.html">conv.rec-mifList</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">conv.rec-pmcmc</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">conv.rec-pmcmcList</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="csnippet.html">Csnippet</a></td>
-<td>C code snippets for accelerating computations</td></tr>
-<tr><td width="25%"><a href="csnippet.html">Csnippet-class</a></td>
-<td>C code snippets for accelerating computations</td></tr>
-</table>
-
-<h2><a name="D">-- D --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="dacca.html">dacca</a></td>
-<td>Model of cholera transmission for historic Bengal.</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">data.array</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">data.array-method</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">data.array-pomp</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pomp.html">data.frame-pomp</a></td>
-<td>Constructor of the basic POMP object</td></tr>
-<tr><td width="25%"><a href="eulermultinom.html">deulermultinom</a></td>
-<td>The Euler-multinomial distributions and Gamma white-noise processes</td></tr>
-<tr><td width="25%"><a href="plugins.html">discrete.time.sim</a></td>
-<td>Plug-ins for state-process models</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">dmeasure</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">dmeasure-method</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">dmeasure-pomp</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">dprior</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">dprior-method</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">dprior-pomp</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">dprocess</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">dprocess-method</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">dprocess-pomp</a></td>
-<td>pomp low-level interface</td></tr>
-</table>
-
-<h2><a name="E">-- E --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="pfilter.html">eff.sample.size</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">eff.sample.size-method</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">eff.sample.size-pfilterd.pomp</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="plugins.html">euler.sim</a></td>
-<td>Plug-ins for state-process models</td></tr>
-<tr><td width="25%"><a href="sir.html">euler.sir</a></td>
-<td>Compartmental epidemiological models</td></tr>
-<tr><td width="25%"><a href="eulermultinom.html">eulermultinom</a></td>
-<td>The Euler-multinomial distributions and Gamma white-noise processes</td></tr>
-<tr><td width="25%"><a href="example.html">Example pomp models</a></td>
-<td>Examples of the construction of POMP models</td></tr>
-</table>
-
-<h2><a name="F">-- F --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="pfilter.html">filter.mean</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">filter.mean-method</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">filter.mean-pfilterd.pomp</a></td>
-<td>Particle filter</td></tr>
-</table>
-
-<h2><a name="G">-- G --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="plugins.html">gillespie.sim</a></td>
-<td>Plug-ins for state-process models</td></tr>
-<tr><td width="25%"><a href="sir.html">gillespie.sir</a></td>
-<td>Compartmental epidemiological models</td></tr>
-<tr><td width="25%"><a href="gompertz.html">gompertz</a></td>
-<td>Gompertz model with log-normal observations.</td></tr>
-</table>
-
-<h2><a name="I">-- I --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="lowlevel.html">init.state</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">init.state-method</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">init.state-pomp</a></td>
-<td>pomp low-level interface</td></tr>
-</table>
-
-<h2><a name="L">-- L --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="mif.html">logLik-method</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="nlf.html">logLik-method</a></td>
-<td>Parameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)</td></tr>
-<tr><td width="25%"><a href="pfilter.html">logLik-method</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">logLik-method</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="probe.html">logLik-method</a></td>
-<td>Probe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.</td></tr>
-<tr><td width="25%"><a href="traj-match.html">logLik-method</a></td>
-<td>Parameter estimation by fitting the trajectory of a model's deterministic skeleton to data</td></tr>
-<tr><td width="25%"><a href="mif.html">logLik-mif</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="nlf.html">logLik-nlfd.pomp</a></td>
-<td>Parameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)</td></tr>
-<tr><td width="25%"><a href="pfilter.html">logLik-pfilterd.pomp</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">logLik-pmcmc</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="probe.html">logLik-probed.pomp</a></td>
-<td>Probe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.</td></tr>
-<tr><td width="25%"><a href="traj-match.html">logLik-traj.matched.pomp</a></td>
-<td>Parameter estimation by fitting the trajectory of a model's deterministic skeleton to data</td></tr>
-<tr><td width="25%"><a href="logmeanexp.html">logmeanexp</a></td>
-<td>The log-mean-exp trick</td></tr>
-<tr><td width="25%"><a href="LondonYorke.html">LondonYorke</a></td>
-<td>Historical childhood disease incidence data</td></tr>
-</table>
-
-<h2><a name="M">-- M --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="pomp.html">matrix-pomp</a></td>
-<td>Constructor of the basic POMP object</td></tr>
-<tr><td width="25%"><a href="proposals.html">MCMC proposal distributions</a></td>
-<td>MCMC proposal distributions</td></tr>
-<tr><td width="25%"><a href="proposals.html">MCMC proposal functions</a></td>
-<td>MCMC proposal distributions</td></tr>
-<tr><td width="25%"><a href="mif.html">mif</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="mif.html">mif-class</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="mif.html">mif-method</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="mif.html">mif-methods</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="mif.html">mif-mif</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="mif.html">mif-pfilterd.pomp</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="mif.html">mif-pomp</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="mif.html">mifList-class</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="proposals.html">mvn.diag.rw</a></td>
-<td>MCMC proposal distributions</td></tr>
-<tr><td width="25%"><a href="proposals.html">mvn.rw</a></td>
-<td>MCMC proposal distributions</td></tr>
-</table>
-
-<h2><a name="N">-- N --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="nlf.html">nlf</a></td>
-<td>Parameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)</td></tr>
-<tr><td width="25%"><a href="nlf.html">nlf-method</a></td>
-<td>Parameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)</td></tr>
-<tr><td width="25%"><a href="nlf.html">nlf-nlfd.pomp</a></td>
-<td>Parameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)</td></tr>
-<tr><td width="25%"><a href="nlf.html">nlf-pomp</a></td>
-<td>Parameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)</td></tr>
-<tr><td width="25%"><a href="nlf.html">nlfd.pomp-class</a></td>
-<td>Parameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)</td></tr>
-<tr><td width="25%"><a href="nlf.html">Nonlinear forecasting</a></td>
-<td>Parameter estimation my maximum simulated quasi-likelihood (nonlinear forecasting)</td></tr>
-<tr><td width="25%"><a href="pomp.html">numeric-pomp</a></td>
-<td>Constructor of the basic POMP object</td></tr>
-</table>
-
-<h2><a name="O">-- O --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="pomp-methods.html">obs</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">obs-method</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">obs-pomp</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="plugins.html">onestep.dens</a></td>
-<td>Plug-ins for state-process models</td></tr>
-<tr><td width="25%"><a href="plugins.html">onestep.sim</a></td>
-<td>Plug-ins for state-process models</td></tr>
-<tr><td width="25%"><a href="ou2.html">ou2</a></td>
-<td>Two-dimensional discrete-time Ornstein-Uhlenbeck process</td></tr>
-</table>
-
-<h2><a name="P">-- P --</a></h2>
-
-<table width="100%">
-<tr><td width="25%"><a href="parmat.html">parmat</a></td>
-<td>Create a matrix of parameters</td></tr>
-<tr><td width="25%"><a href="pfilter.html">particle filter</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">partrans</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">partrans-method</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">partrans-pomp</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="bsplines.html">periodic.bspline.basis</a></td>
-<td>B-spline bases</td></tr>
-<tr><td width="25%"><a href="pfilter.html">pfilter</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">pfilter-method</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">pfilter-pfilterd.pomp</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">pfilter-pomp</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">pfilterd.pomp-class</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="abc.html">plot-abc</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="abc.html">plot-abcList</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="bsmc.html">plot-bsmcd.pomp</a></td>
-<td>The Liu and West Bayesian particle filter</td></tr>
-<tr><td width="25%"><a href="abc.html">plot-method</a></td>
-<td>Estimation by approximate Bayesian computation (ABC)</td></tr>
-<tr><td width="25%"><a href="bsmc.html">plot-method</a></td>
-<td>The Liu and West Bayesian particle filter</td></tr>
-<tr><td width="25%"><a href="mif.html">plot-method</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">plot-method</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">plot-method</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="probe.html">plot-method</a></td>
-<td>Probe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.</td></tr>
-<tr><td width="25%"><a href="mif.html">plot-mif</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="mif.html">plot-mifList</a></td>
-<td>Maximum likelihood by iterated filtering</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">plot-pmcmc</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">plot-pmcmcList</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">plot-pomp</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="probe.html">plot-probe.matched.pomp</a></td>
-<td>Probe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.</td></tr>
-<tr><td width="25%"><a href="probe.html">plot-probed.pomp</a></td>
-<td>Probe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.</td></tr>
-<tr><td width="25%"><a href="probe.html">plot-spect.pomp</a></td>
-<td>Probe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.</td></tr>
-<tr><td width="25%"><a href="plugins.html">plugins</a></td>
-<td>Plug-ins for state-process models</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">pmcmc</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">pmcmc-class</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">pmcmc-method</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">pmcmc-methods</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">pmcmc-pfilterd.pomp</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">pmcmc-pmcmc</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">pmcmc-pomp</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="pmcmc.html">pmcmcList-class</a></td>
-<td>The particle Markov chain Metropolis-Hastings algorithm</td></tr>
-<tr><td width="25%"><a href="pomp.html">pomp</a></td>
-<td>Constructor of the basic POMP object</td></tr>
-<tr><td width="25%"><a href="pomp.html">pomp constructor</a></td>
-<td>Constructor of the basic POMP object</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">pomp low-level interface</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">pomp methods</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pomp-package.html">pomp package</a></td>
-<td>Inference for partially observed Markov processes</td></tr>
-<tr><td width="25%"><a href="simulate-pomp.html">POMP simulation</a></td>
-<td>Simulations of a partially-observed Markov process</td></tr>
-<tr><td width="25%"><a href="pomp.html">pomp-class</a></td>
-<td>Constructor of the basic POMP object</td></tr>
-<tr><td width="25%"><a href="pomp.html">pomp-method</a></td>
-<td>Constructor of the basic POMP object</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">pomp-methods</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pomp.html">pomp-pomp</a></td>
-<td>Constructor of the basic POMP object</td></tr>
-<tr><td width="25%"><a href="example.html">pompExample</a></td>
-<td>Examples of the construction of POMP models</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">pompLoad</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">pompLoad-method</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">pompLoad-pomp</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">pompUnload</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">pompUnload-method</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="lowlevel.html">pompUnload-pomp</a></td>
-<td>pomp low-level interface</td></tr>
-<tr><td width="25%"><a href="spect.html">Power spectrum computation and matching</a></td>
-<td>Power spectrum computation and spectrum-matching for partially-observed Markov processes</td></tr>
-<tr><td width="25%"><a href="spect.html">power spectrum computation and matching</a></td>
-<td>Power spectrum computation and spectrum-matching for partially-observed Markov processes</td></tr>
-<tr><td width="25%"><a href="pfilter.html">pred.mean</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">pred.mean-method</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">pred.mean-pfilterd.pomp</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">pred.var</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">pred.var-method</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pfilter.html">pred.var-pfilterd.pomp</a></td>
-<td>Particle filter</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">print-method</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="pomp-methods.html">print-pomp</a></td>
-<td>Functions for manipulating, displaying, and extracting information from objects of the 'pomp' class</td></tr>
-<tr><td width="25%"><a href="probe.html">probe</a></td>
-<td>Probe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.</td></tr>
-<tr><td width="25%"><a href="basic-probes.html">Probe functions</a></td>
-<td>Some useful probes for partially-observed Markov processes</td></tr>
-<tr><td width="25%"><a href="basic-probes.html">probe functions</a></td>
-<td>Some useful probes for partially-observed Markov processes</td></tr>
-<tr><td width="25%"><a href="probe.html">probe-method</a></td>
-<td>Probe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.</td></tr>
-<tr><td width="25%"><a href="probe.html">probe-pomp</a></td>
-<td>Probe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.</td></tr>
-<tr><td width="25%"><a href="probe.html">probe-probed.pomp</a></td>
-<td>Probe a partially-observed Markov process by computing summary statistics and the synthetic likelihood.</td></tr>
-<tr><td width="25%"><a href="basic-probes.html">probe.acf</a></td>
-<td>Some useful probes for partially-observed Markov processes</td></tr>
-<tr><td width="25%"><a href="basic-probes.html">probe.ccf</a></td>
-<td>Some useful probes for partially-observed Markov processes</td></tr>
-<tr><td width="25%"><a href="basic-probes.html">probe.marginal</a></td>
-<td>Some useful probes for partially-observed Markov processes</td></tr>
[TRUNCATED]

To get the complete diff run:
    svnlook diff /svnroot/pomp -r 1134

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