Comments (2)
So you mean to define glm.hit1
and then give that same model to all three nodes? I think I see where you're going with that, because all three are based on the points up to that moment in the game and the highUpcard
. But to make this work, at the very least, we'd have to map the names from the model to the network structure. We could probably provide a utility to do that, but I think we'd end up refitting the models underneath the hood somewhere anyway. And I worry that this would be one of those things where we might have our "intended" purpose, but when released to a wider user base, it may not get used as intended, prove to be buggy and cause errors, and result in people abandoning the package.
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I'll add that, after thinking about this some more, the copy of models idea should be avoidable once we go to Markov dynamic Bayesian networks.
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Related Issues (20)
- Change JAGS parameter names to R parameter names HOT 2
- Change HydePosterior to HydeSim
- Update documentation in `setNode`
- setNode dbern bug HOT 4
- Error when data is tibble HOT 3
- Inaccurate HydeSim() predictions with discrete nodes
- Truncated normal distribution HOT 1
- `setNode` doesn't have a `nodeData` argument.
- `bindPosterior` should retain an index for chain number HOT 4
- Store network images in vignettes as PNGs HOT 5
- Formula checking error HOT 4
- [!] logit() and the VGAM package HOT 4
- Stan Integration
- ArgumentCheck error in setNode() HOT 1
- Changing graph layout
- Adding observed nodes to compileDecisionModel() HOT 3
- Changes in upcoming v0.8 release of `DiagrammeR` package will require changes in `plot.HydeNetwork` HOT 3
- Relaxing some decision/utility node constraints HOT 6
- policyMatrixValues() returns null HOT 1
- Categorical interactions are not handled correctly
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