Constant-Parameters-History.org

@@ -2,7 +2,10 @@
 
 Created by Alexander Zarebski
 
-Last edited using =BEAST v2.6.7= and =timtam v0.3.1=.
+Last edited using
+- =BEAST v2.7.1=
+- =remaster v1.0.0=
+- =timtam v0.4.0=
 
 This tutorial demonstrates how to use TimTam to estimate the reproduction number
 and prevalence of infection at two points in time using a sequence alignment and
@@ -50,8 +53,8 @@ time series that we will use.
 
 These data were simulated with [[http://tgvaughan.github.io/MASTER][MASTER]], with parameters chosen so the epidemic
 has a basic reproduction number of \(1.85\). To simplify this tutorial we will
-assume a known net removal rate, denoted by [[https://github.com/aezarebski/timtam2/wiki/Glossary#sigma][sigma]], of (\(0.054 = 0.046 +
-0.008\)), and the pathogen evolves with a substitution rate of (\(10^{-3}\))
+assume a known net removal rate, denoted by [[https://github.com/aezarebski/timtam2/wiki/Glossary#sigma][sigma]], of (\(0.1 = 0.046 + 0.008 +
+0.046\)), and the pathogen evolves with a substitution rate of (\(10^{-3}\))
 substitutions/site/day constantly across the tree. Both values fall within the
 ballpark of what might be expected for an RNA virus. The origin time for our
 simulated epidemic took place (\(70\)) days before the end of the simulation.
@@ -127,7 +130,7 @@ estimated.
 1. Run MCMC by executing the XML file on BEAST (you may want to grab a coffee
    while this is running.)
 2. Download the simulation data (which is needed for subsequent visualisations)
-   in [[https://github.com/aezarebski/timtam2/wiki/tutorial-7/tutorial-7-simulation-output.json][tutorial-7-simulation-output.json]] and make sure it is in your working
+   in [[https://github.com/aezarebski/timtam2/wiki/tutorial-7/tutorial-7-simulation-output.traj][tutorial-7-simulation-output.traj]] and make sure it is in your working
    directory.
 3. Plot the results using [[https://github.com/aezarebski/timtam2/wiki/tutorial-7/post-processing.R][post-processing.R]]. This will produce two figures
    similar to the ones shown below, summarising some of the epidemiological