update ASM post

_posts/2024-08-01-automatic-stopping-mcmc.md

@@ -34,7 +34,7 @@ Since it is not possible beforehand to determine whether a parameter should be i
 When all stopping criteria pass, the MCMC stops and produces a combined trace and tree logs with burn-in removed from the two independent MCMC chains.
 So, there should be no more need to resume an MCMC analysis when using the ASM method.
 
-For more details, see Berling et al, 2023.
+For more details, see [Berling et al, 2024](https://doi.org/10.1109/TCBB.2024.3457875).
 
 ## In practice
 
@@ -47,6 +47,60 @@ You can set parameters by clicking the TreePSRF button for the Gelman-Rubin-like
 
 <img width="916" alt="asm-options" src="https://raw.githubusercontent.com/rbouckaert/asm/main/doc/asm-options.png">
 
+## Interpreting screen output
+
+Screen output may look something like this:
+
+```
+Check 19   burnin:[14, 14]psrf1mean = 1.472 reset start -1 10.0 5.1 10.0 :5.1  in 5 mseconds
+Check 20   burnin:[15, 15]psrf1mean = 1.399 reset start -1 7.2 5.3 10.0 :5.3   in 5 mseconds
+Check 21   burnin:[15, 15]psrf1mean = 1.426 reset start -1 10.9 7.2 12.0 :7.2  in 5 mseconds
+Check 22   burnin:[16, 16]psrf1mean = 1.466 reset start -1 12.0 12.0 12.0 :12.0      in 3 mseconds
+Check 23   burnin:[17, 17]psrf1mean = 1.525 reset start -1 8.8 12.0 8.9 :8.8   in 7 mseconds
+Check 24   burnin:[18, 18]psrf1mean = 1.504 reset start -1 7.6 12.0 6.9 :6.9   in 18 mseconds
+```
+
+Let’s have a look at the first entry:
+
+```
+Check 19   burnin:[14, 14]psrf1mean = 1.472 reset start -1 10.0 5.1 10.0 :5.1  in 5 mseconds
+```
+
+**Check 19**   check number
+
+**burnin:[14, 14]** log items removed as burnin, first number for chain1, second for chain2
+
+**psrf1mean = 1.472**  potential scale reduction factor — this statistic represents a Gelman-Rubin like statistic for the trees. It should go towards 1 at convergence.
+
+**reset start -1** whether the start of the psrf is recalculated from the start
+
+**10.0 5.1 10.0** ESSs of the statistics specified in the `asm.inference.TraceESS` statistic
+
+**:5.1** minimum of the ESSs of the `asm.inference.TraceESS statistic`. This should go to the threshold specified in the `targetESS` attribute.
+
+**in 5 mseconds** time used to calculate the statistics
+
+
+## Sampling from prior
+
+Normally, to get a sample from the prior for an MCMC run, the `-sampleFromPrior` flag can be used for BEAST.
+This fails with ASM, so to obtain a sample from the prior, the XML must be edited to produce a sample from the prior, like so:
+
+* move the element with `id="likelihood"` including all of its sub-elements to outside the `run` element, say at the end of the file, just before the `</beast>` line.
+* remove `likelihood` from the `traces` attribute of the `TraceESS` stopping criterion.
+
+
+If you get this kind of error:
+
+```
+Check 0 java.lang.IllegalArgumentException: Could not find label likelihood in trace log. Use one of [Sample, posterior, prior, ...
+```
+
+the `traces` attribute is not specified, and the default (i.e. `posterior,likelihood,prior`) will be used. To fix this the `traces="posterior,prior"` must be added to the `TraceESS` stopping criterion, so it looks something like
+
+```
+<stoppingCriterion spec="asm.inference.TraceESS" targetESS="100" traces="posterior,prior"/>
+```
 
 
 ## References