Hi, all,
assuming a and b are random variables and their pdf f(a) and f(b) are known. then, how do I solve for the definite integral given as v=\int\limits_{a}^{b} g(x) dx, where g(x) is a function of x? or, how do I solve the pdf of v?
Thanks a lot..
Hi, all,
Let's assume a random variable's variance is zero as sample size tends to infinity somehow, can I say that its higher order central moments are also zero as the sample size tends to infinity?
Thks a lot
what I am trying to solve is the desnity function of f(x|t1<x<t2), therefore, its intergral over the support should be 1. What you gave me seems should be devided by 1/(F(t2)-F(t1)) (and you mentioned that), however, since t2 and t1 are random, I use its expectation instead. That's to say, the...
Hi, all,
I would to solve an integral equation, here is the form
f(x)=\int_{x}^{R}K(x,t)g(t)dt
f(x) and g(t) are known function, R is an constant, how to compute the unknown Kernel
K(x,t)?
Thanks a lot
I did a couple of simulations and found that the pdf f(x|t1<x<t2) seems need to be scaled. Maybe I have miss out some conditions, say the support of x, t1 and t2 are all [0,R]. In this case, how do I compute the truncated pdf? Thanks a lot.
Hi, all,
I am having a problem in calculating a randomly truncated pdf. Let x be a random variable, it's pdf f(x) is known. Let t1 and t2 be anther two random variables, their pdf f(t1) and f(t2) are known as well. Now, how do I compute the pdf f(x|t1<x<t2)?
Thks a lot.
Hi,all,
I have a problem of computing pdf of some random variables. Assuming x1, x2... xN are some random variables. Now, I know the pdf of x1, which is f(x1). For the pdf of x2, it is given as a function of x1, in this case, how do I compute pdf of x2? Or, rather, how do I generate samples...
Hi, all,
Let's say we deploy some random points on a line of finite length according to a poisson distribution of density \lambda. Can I say that these points are also "uniformly" distributed on the same line?
thks
Hi, All,
Let x1 x2... Xn be correlated random events (or variables). Say P(X1), P(X2)..., P(Xn) can be computed, in addition to that, covariance and correlated between all X can be computed. My question is, what is P(X1) * P(X2) *... * P(Xn)?