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| I know I'm a bit late to this party, but for anyone who still has the same question in 2019: I wrote a repository functions specifically for this: [KullbackLeiblerDivergence on the Wolfram Function Repository][1]. It should work for all sorts of... |
| If you include the `a=2` definition in the `Initialization` and set `SaveDefinitions -> True`, it should work, I think. Unfortunately I don't have time right now to give a better explanation than that, but I hope it works. You can always try to make... |
| I completely agree with this. Personally, I think that something along the lines of Haskell-style lazy lists fits best with WL's paradigms. In the past I did an exercise to try an implement this [from scratch][1], though I'm aware that similar... |
| Looks like a bug to me. I would expect D[{p1 + a t, p2 + b t}, {t, k}] /. k -> 0 to return the same as D[{p1 + a t, p2 + b t}, {t, 0}] I'll go ahead and report it. |
| One little extra tip I can add, is that you can use `DistributionParameterAssumptions` and `DistributionDomain` to help you with the automatic generation of simplifying assumptions: In[1]:=... |
| Yes, doing things in parallel doesn't always make it faster. There's overhead involved with parallelizing the task. By the looks of it, your parallel timing includes the launch time of the kernels. Have you tried evaluating `LaunchKernels[]` first... |
| That is what `TransformedDistribution` does. It transforms `x`, which is the input variable to the `PDF` of `NormalDistribution[6, 1]`. Yes, this always confuses me as well whenever I haven't worked with probability distributions for a while :). |
| A while ago, I wrote a package that might help you with this problem: lazyLists https://github.com/ssmit1986/lazyLists The idea of a lazy list is that it only generates elements on request. The full documentation is in the example notebook in the... |
| I think you can just use `Quiet` to get rid of the error messages and you should be fine. You can even use `Quiet @ Check[..., 0]` to ensure that any terms that generate messages will be set to zero and don't affect the sum, if you're certain that... |
| You're welcome. I just checked, and you're right: the way the function is evaluated by `FindFit`, it's better to use memoization. I expected it to first evaluate the parameters and then insert the values for `t` (in which case you'd need to do the... |