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 Mar 26 awarded Scholar Mar 26 comment Computing the derivative of a quadratic form and matrix chain rule Thank you for the clarifying remarks. After I had gone back and did some debugging, I found a different reason why the code wasn't converging. In the end, with the derivatives I had calculated, I did get it to converge. Mar 26 accepted Computing the derivative of a quadratic form and matrix chain rule Mar 26 comment An example of a “pathological” power-spectral density function? As an aside, I used to work as a radar engineer, and once an analyst kept grumbling about why his radar simulation was giving him nonsense $\infty$ values. I looked at his code and it was because he was using a non-integrable function for the antenna gain pattern (hence infinite energy radar). When I tried to explain this, he got angry that I was using the word "integrable" (a concept he apparently thought he could forget about after college). Mar 26 comment An example of a “pathological” power-spectral density function? Consider the function $\frac{1}{\sqrt{|f|}}$. The singularity is just barely integrable, but if you square it, then it's no longer integrable. Really, you're looking for function that are in $L^{k}(\mathbb{R})$ for some $k-1$, that doesn't mean $\log(1+ab')$ is well-behaved. I think you have a backward inequality as well. I'm not sure that $\alpha$-stability buys you anything, because you're only ever working with one copy of the distribution. You're not using any central limit theorem type properties, and so all of the suggestions above about how there can be arbitrary probability density on $[b',b'']$ still applies. There's just not much you can possibly say without stronger assumptions. Mar 24 answered On the integral $\int_{b'}^{b''}f(x)\ln(1+a x)\mathrm{d}x$ Mar 24 answered Likelihood Ratio Test for Linear Regression Mar 23 comment Error of Pearson Correlation Coefficient Just as an aside, there are many ways to evaluate fits. No single scoring method is ever "best", and in order to provide informative, truthful results to the readers of your work, you need to usually apply a wide array of model checks and fit scores. One place to start reading is Chapter 6 of the excellent resource book "Bayesian Data Analysis" by Gelman, Carlin, Stern, and Rubin. Mar 23 awarded Enlightened Mar 22 awarded Nice Answer Mar 22 revised Gradient of a Mahalanobis distance added 2 characters in body Mar 22 revised Gradient of a Mahalanobis distance deleted 117 characters in body Mar 22 revised Gradient of a Mahalanobis distance edited body Mar 22 answered Gradient of a Mahalanobis distance