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visits member for 3 years, 10 months
seen Apr 28 at 20:01

May
24
comment Characterization of proper maps using filters
@PatrickDaSilva I believe I wanted to say that either $A$ or its complement is in $\mathcal U$. Sorry about that.
May
23
asked Characterization of proper maps using filters
May
23
accepted Dense implies strictly dense in TOP
May
23
comment Dense implies strictly dense in TOP
I was thinking about proving that $\overline{O \cap X} = \bar O$. Looks like my thoughts were in the right direction. Thanks.
May
23
revised Dense implies strictly dense in TOP
added 233 characters in body
May
23
asked Dense implies strictly dense in TOP
May
13
awarded  Caucus
Jan
29
accepted Filters and sequences
Jan
29
asked Filters and sequences
Dec
4
comment Probability density function of $\sigma X + \mu$.
Oops. Yeah, you guys are right. What I am wondering now is how you are dealing with the $\sigma < 0$ case.
Dec
4
comment How to prove these three norm equivalence problems
These are matrix norms: en.wikipedia.org/wiki/Matrix_norm
Dec
4
comment Probability density function of $\sigma X + \mu$.
For one thing, you expect that $\int_{\mathbb R} f_Z(x) \, dx = 1$, but if you use the formula for $f_Z(x)$ that you have, you don't get 1.
Dec
4
comment Poisson distribution and probability of random variables
I am not understanding your problem. You have the formulas you need: just replace $\lambda$ with 5 and simplify.
Dec
4
comment Let $f(z)=e^x + ie^{2y}$ where $z=x+iy$. Where does $f'(z)$ exist?
I think you just answered your own question: f'(z) exists if and only if x = log 2 + 2y.
Dec
4
comment Independence of an event with null probability with another event.
Example: Suppose X is uniformly distributed on [0,1]. Let A be the event X = 0.6 and let B be the event X > 0.5 Then P(B) = 0.5 and P(B|A) = 1, event though P(A) = 0.
Dec
4
comment Independence of an event with null probability with another event.
What do you find unsatisfactory about it? I find it unsatisfactory from the following point-of-view: If A and B are independent, I excpect P(B|A) = P(B). However, this only makes sense when P(A) is not 0.
Nov
7
comment Unbiased estimates and cluster points
You are right about that. Hmm...I am trying to get a feel for what unbiased means in terms of actual data. I guess I will have to think harder.
Nov
7
asked Unbiased estimates and cluster points
Oct
31
accepted Components of a k-regular bipartite graph
Sep
8
comment Finding the MLE for parameter $\theta$ from distribution of the form $e^{-|x-\theta|}$
What exactly is your first question? For the second question, I would set $\alpha = e^{1/\theta}$, solve for $\theta$, plug that in $f(x|\theta)$ and find the MLE.