I wonder how to use mixstock package

I'm studing a mixed stock analysis based on walkthrough provided by Bolker (https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=043730a02b148396ebd54b2f62e8f6364714b1b2), using the 'mixstock' package.

I had some problems while practicing the package. An error occurred in the process of graphing the many-to-many analysis, so the graph presented in the example does not appear. Could you possibly solve that problem?

i want to make this graph, but

My code made this graph.

This is my code.

Z = simmixstock2(nsource=4,nmark=5,nmix=3,
          sourcesize=c(4,2,1,1),
          sourcesampsize=rep(25,4),
          mixsampsize=rep(30,3),rseed=1001)
Zfit0 = mm.wbugs(Z,sourcesize=c(4,2,1,1),returntype="bugs")
plot(as.mcmc.bugs(Zfit0))
plot(Zfit0)

Also, can I put my own data other than random data into the "simmixstock2" command? I want to do it once with my data, but the manual command seems to generate it only randomly, so I would like to know if there is a way. thank you.

This works for me:

library(mixstock)
Z = simmixstock2(nsource=4,nmark=5,nmix=3,
          sourcesize=c(4,2,1,1),
          sourcesampsize=rep(25,4),
          mixsampsize=rep(30,3),rseed=1001)
Zfit0 = mm.wbugs(Z,sourcesize=c(4,2,1,1), pkg="JAGS", jags.seed = 101)
plot(Zfit0)

The changes are

• use JAGS instead of WinBUGS (which may be nearly obsolete - in any case, hard to run on platforms other than Windows; I don't know the status of OpenBUGS), including setting the seed for the MCMC run
• don't specify returntype = "bugs" (instead, the default "mixstock" option gives something that we can plot)

I'm not quite sure what you mean by

> can I put my own data other than random data into the "simmixstock2" command ?

The simmixstock2() function is designed for simulating data in the case where you want to see how things work when you don't have your own data. There are instructions in the vignette/walkthrough on pp. 4-5 about how to input data for multiple mixed stocks (add them as additional columns to a matrix (with rows = haplotypes, columns = sources and mixed stocks) and specify the number of mixed stocks (nmix=1 by default) when using as.mixstock.data()).