Cdectree_expected_values and dectree_expected_values give different results

[jogwalker]

Hi, I have been playing around with this package and trying to get it to work for quite a big decision tree which would be a huge hassle to manually calculate expected probabilities. It looks like in dectree_expected_values all endpoint nodes are given their inputted cost value directly, while in Cdectree_expected_values, endpoint nodes have a value of 0.

[n8thangreen]

Hi Josephine (I think!), there are certainly inconsistencies with this. I've basically just kept adding bits to it over quite a bit of time whenever I needed something for a project so theres very little overall design decision. Its great that you're trying it out tho! I should sort it out so this is a good excuse. Can you send me the example you've tried which gives the problem please and I'll fix it... n.green[at]ucl.ac.uk

[jogwalker]

Hi Nathan Thanks! The difference can be seen using your examples ("cost" and "probs")

mt <- define_model(transmat=list(vals=cost,prob=probs)) dectree_expected_values(model=mt)

1 2 3 4 5 6 7 5.6 12.8 3.8 10.0 1.0 10.0 1.0

Cdectree_expected_values(vals=as.matrix(cost),p=as.matrix(probs))

[1] 5.6 2.8 2.8 0.0 0.0 0.0 0.0 Are you able to clarify whether this is a different output being calculated or does one of them have an error? Also, I thought that the value for node 1 should be equivalent to the below, but perhaps I'm calculating something different or incorrectly?

probs[1,2]*cost[1,2]*probs[2,4]*cost[2,4] +

probs[1,2]*cost[1,2]*probs[2,5]*cost[2,5] + + probs[1,3]*cost[1,3]*probs[3,6]*cost[3,6] + probs[1,3]*cost[1,3]*probs[3,7]*cost[3,7] 2 1 7.84 I can get 2.8 like this: probs[1,2]*cost[2,4]*probs[2,4] + probs[1,2]*cost[2,5]*probs[2,5] + probs[1,3]*cost[3,6]*probs[3,6] + probs[1,3]*cost[3,7]*probs[3,7] Or 12.8 like this: cost[1,2] + probs[1,2]*cost[2,4]*probs[2,4] + probs[1,2]*cost[2,5]*probs[2,5] + probs[1,3]*cost[3,6]*probs[3,6] + probs[1,3]*cost[3,7]*probs[3,7] Also, just to note that in my transition matrix I had some probabilities that were repeating decimals. This meant that some of the functions weren't working because is_prob_matrix(test[["prob"]]) was returning FALSE even though when I looked at the value it looked like a 1! So I rounded all my probabilities (to 6 decimal places) and it works fine now. Thanks again Josephine

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On Mon, Nov 16, 2020 at 3:44 PM Dr Nathan Green ***@***.***> wrote: Hi Josephine (I think!), there are certainly inconsistencies with this. I've basically just kept adding bits to it over quite a bit of time whenever I needed something for a project so theres very little overall design decision. Its great that you're trying it out tho! I should sort it out so this is a good excuse. Can you send me the example you've tried which gives the problem please and I'll fix it... n.green[at]ucl.ac.uk — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#6 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AA7OI6L2T2YHT6SJXA753P3SQFCFZANCNFSM4TXH7EEQ> .