User Portlet
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| A brute force way is to plug in integer values for $x$ and $y$ and you'll find that $f(x)=0$ for even $x$. For odd $x$ you'll find that $f(x)=-2 i^{x+1}$. One such real valued function that has such properties is $\sin \left(\frac{\pi ... |
| I think a direct integration over the conditioned area works: (* Set parameters *) m = 1/16; t = 3/4; (* Mean by integration *) bMean = Integrate[b, {a, m, m + 1}, {b, 0, Min[a/t, 1]}]/ Integrate[1, {a,... |
| There are not enough `PlotPoints`. Try Plot[Sum[i, {i, 1, n}], {n, 1, 50}, PlotPoints -> 100] or ListStepPlot[Table[Sum[i, {i, 1, n}], {n, 1, 50}]] |
| Think about it a bit more. Yes, it isn’t the result that you expected. Note that your “data” is clearly contrived and not a random sample from any distribution. You’ve purposely made the “data” perfectly symmetric about the mean. Why would you... |
| You don't mention the steps you followed when using `InstallR`, but when I followed the documentation in `RLink/tutorial/ConfigureExternalRInstallation`, I was able to load already installed libraries. I used the following for an older version of... |
| Which is best depends on what you mean by "best", your subject matter, and your objective. Because you appear to be selecting between a Gamma and a Nakagami distribution, I would assume that there is no theoretical reason for either. As Henrik... |
| Would you edit the code so that it can be pasted into a notebook? Alternatively, attaching a notebook would be helpful. What you've given is missing a few backslashes. For example: `[Alpha]` instead of `\[Alpha]`. |
| I'm not understanding or believing what you mean by "Sometimes the PDF is plotted at different scale...." Could you give an example? Also, adding "PlotRange -> All" will fix any cropping of the PDF. |
| That message is a "warning" rather than an "error" as you see you still get a good fit. However, the underlying reason for the warning is that your model is overparametersized. If you look at the parameter correlation matrix you see the following: ... |
| When using the command with symbolic parameters for a normal distribution KolmogorovSmirnovTest[data, NormalDistribution[\[Mu], \[Sigma]], "TestData"] you are testing whether the data comes from a normal distribution. That is the... |