However, it's not possible to set the value of a productPatameter as there's no telling what the values of each parameter in the product would be; hence the following error is generated:
Exception in thread "Thread-1" java.lang.RuntimeException: Not implemented
at dr.inference.model.ProductParameter.setParameterValue(ProductParameter.java:77)
at dr.app.checkpoint.BeastCheckpointer.readStateFromFile(BeastCheckpointer.java:415)
at dr.app.checkpoint.BeastCheckpointer.loadState(BeastCheckpointer.java:124)
at dr.inference.mcmc.MCMC.chain(MCMC.java:169)
at dr.inference.mcmc.MCMC.run(MCMC.java:137)
at java.lang.Thread.run(Thread.java:745)
Would suggest to modify the XML structure (and update the syntax rules) to mimic that of a GLM, if that's possible.
Currently, performing BSSVS on a skygrid+covariates model involves defining a productParameter first:
However, it's not possible to set the value of a productPatameter as there's no telling what the values of each parameter in the product would be; hence the following error is generated: Exception in thread "Thread-1" java.lang.RuntimeException: Not implemented at dr.inference.model.ProductParameter.setParameterValue(ProductParameter.java:77) at dr.app.checkpoint.BeastCheckpointer.readStateFromFile(BeastCheckpointer.java:415) at dr.app.checkpoint.BeastCheckpointer.loadState(BeastCheckpointer.java:124) at dr.inference.mcmc.MCMC.chain(MCMC.java:169) at dr.inference.mcmc.MCMC.run(MCMC.java:137) at java.lang.Thread.run(Thread.java:745)
Would suggest to modify the XML structure (and update the syntax rules) to mimic that of a GLM, if that's possible.