Recent content by colstat

I was hoping to "make" it positive using some trick, but after looking around again I am wrong. Like you said, if it's NOT positive definite, then it's not. I also realized there's an error when putting together the matrix. So, problem solved I guess.

Suppose I have a matrix that looks like this [,1] [,2] [1,] 2.415212e-09 9.748863e-10 [2,] -2.415212e-09 5.029136e-10 How do I make it positive definite? I am not looking for specific numerical value answer, but a general approach to this problem. I have heard...

I am not using R, but even in R there's an algorithm right? Is there a way to see what they did in the package?

Thank you zlin034. What do you use to simulate copulas, Gaussian and student-t? I have two ideas for bivariate Gaussian: 1. integrate the density from Wiki, here http://en.wikipedia.org/wiki/Copula_(probability_theory)#Gaussian_copula or this...

Hi, all I have been reading about copula, but still very confused. What exactly is a copula? My understanding is: there are couple of components 1. uniform cdf marginal 2. a covariance matrix What exactly is this thing? Why am I calculating the marginals and what does it have to do...

wow, you are really good. Yes, I wrote a simplified version of inverse-gamma. I am looking for the posterior distribution.

Homework Statement How do you integrate this? x-ae-b/x, where a and b are some constants. The Attempt at a Solution I have tried this http://integrals.wolfram.com/index.jsp?expr=x+*+e^%28-1%2Fx%29&random=false Is there a closed form of this?

I was wondering about this, since the researcher himself said "binomial distribution z statistics with continuity correction." Also, he said "The P values were calculated by comparing the observed proportion based on 29 patients..." I am just thinking...what in the world?! why? The article...

thanks! :) So, why am I told to use normal approximation to the binomial. I understand the normal part, but not the binomial part, where that does binomial come from? Here is another site that actually explains it, but I am still confused...

What test or distribution should I use for before and after treatment? Say, I have 30 subjects I test their blood before and after a pill they take a pill, what kind of test should I use? I want to test mean difference, so, paired t-test? or Wilcoxon signed rank test? The data looks like this...

Why is limit point called a limit point? does it have to do with limits? I know if you talk intervals on a real line in 1-d, you can talk convergence. But when we talk about 2-d, like open balls, why are we calling it limit point, even the definition of a limit point does not mention anything...

hey, Fredrik. I figured it out. Yes, this is the ultrametric space. Thanks, just wanted to know I am thinking right. For the standard metric. If I have a closed ball, is the interior point same the limit point? I mean the definition of interior point is, open ball B(x,r) is contained in...

thanks a lot, Deveno. To prove an open ball B(x,r) is also closed. Is it ok to start like this? Let p be a limit point of B(x,r). If p\notinB(x,r), then, p\inB^{c}(x,r). Where I said "let p be a limit point of B(x,r)." I though limit point only existed in closed balls, but B(x,r)...

wow, that was such a long post. When you say an open set is a union of open balls. How do you actually write that in proof? For all x \in X, there is a ε>0, such that B(x,r) is completely contained in E. Does this look good?

yessss, that makes sense to me. What exactly is an open set, what is its role in all this? I have read it in Rudin and Wiki. It's saying... say, we are in some space E, we have a point y≠x such that d(x,y)<ε. Another way is to say that every open ball B(x,ε) is completely contained in E...