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Mar
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awarded  Nice Answer
Mar
23
comment Why does “convex function” mean “concave *up*”?
@Wangyan So is the question.
Feb
24
comment Joint probability distribution of functions of random variables
This is Calculus, pure and simple. One way to approach it is through differential forms, as explained at stats.stackexchange.com/questions/180715/….
Feb
7
comment Approximating the number $e$ through computer simulation - mathematical background
Re (1) This seems like an ambiguous criterion. If we make sure to generate random variates sufficiently slowly, then (according to it) the calculation will be "Monte Carlo". How about if I time the effort to compute the head and then take twice as much time to generate a Monte-Carlo estimate of the tail--that would seem to qualify as a "Monte Carlo" calculation by this criterion. (2) The tail CDF has a simple closed form expression. Regardless, there are many ways to generate random variables from it.
Feb
7
comment Approximating the number $e$ through computer simulation - mathematical background
+1 Re the final paragraph: You almost got the point, but it's the opposite of what you state. We can generalize this method and simulate, say, $\sum_{i=n+1}^\infty 1/i!$ and add $1+1+1/2+\cdots+1/n!$ to it to estimate $e$. As $n$ increases this becomes extremely efficient, to the point where no iterations of the simulation are needed. Thus, there is a sequence of simulations that range from this "pretty terrible way" to methods requiring no iterations at all. At what point, exactly, do we stop calling this "simulation" and start calling it pure "calculation"? :-)
Feb
2
comment integral of trace function
That tells us you are unfamiliar with the multivariate Gaussian integral. That's fine--you can look it up in various places, such as en.wikipedia.org/wiki/….
Feb
2
comment integral of trace function
Would it help to recognize that $\operatorname{tr}(\mu\mu^\prime\Sigma)=\mu^\prime\Sigma\mu$ (assuming $\mu$ is a column vector)?
Jan
21
comment Relation between differential geometry and differential geodesy
Your edit appears to answer the question.
Dec
28
revised Calculate the Gamma function Γ(2.7)
edited tags
Dec
28
comment Calculate the Gamma function Γ(2.7)
@Lauren Numerical analysts have found that a far better technique is to use the functional relationship $\Gamma(n) = \Gamma(n+1)/n$ repeatedly until $n+1$ is so large that Stirling's approximation to $\Gamma(n+1)$ is sufficiently accurate. Very few of these steps are needed: using five terms in the asymptotic series and stopping as soon as $n+1 \ge 6$ gives ten decimal digits of precision.
Dec
16
awarded  Nice Answer
Dec
15
reviewed Approve To prove a equality of field norm by field extension.
Dec
15
reviewed Reject How to find the center of an ellipse?
Aug
31
comment How to solve for the matrix $X$ in the following equation $AXB + X = CD$
It's a system of linear equations--solve it as you would any system.
Aug
25
awarded  Yearling
Jun
25
comment What are the odds that the pattern, win lose lose, will happen 23 times in a row (69 rounds)?
Thank you: we appreciate your respect for not double-posting on SE sites.
Jun
25
comment What are the odds that the pattern, win lose lose, will happen 23 times in a row (69 rounds)?
(Migrating to Mathematics by request of the OP.)
Jun
11
comment What are the odds that the pattern, win lose lose, will happen 23 times in a row (69 rounds)?
This problem actually is much easier than any of the related ones. Your questions are answered simply by applying the definition of independence (which is what you must assume to answer them without further assumptions): the probabilities of independent events multiply. So go ahead and do the multiplications. You will notice that although the patterns will determine the probabilities, they do not change the fact that in every case you just multiply them all, so there really is nothing here involving combinatorial issues.
May
19
comment Proof for Mean of Geometric Distribution
Your reference gives three distinct derivations. The other two seem to answer your question.