Yes, I know your logic. But I found the marginal expression today. I put it here. I wanna know is it correct, or under what condition I can get F(x) that way?
If there are X and Y two random variables. The pdf of Y is f(y), and conditional pdf of X is f(x|y). I want to find the marginal CDF of X, the F(x). Is this correct?
F(x)=\int^{F(x|y)}_{-\infty}f(y)dy
\dfrac{d}{dx}\int^{F(x|y)}_{-\infty}f(y)dy=\int^{\infty}_{-\infty}f(x|y)f(y)dy=f(x)?
I don't know if this is possible or not, let's see if this is a fun problem.
Let X_1 and X_2 be 2 independent normal random variables. They have different means and variances, and they are independent. I want to have a function that inputs X_1 and X_2, and it has a F distribution with degree of...
For a simple linear model:
\alpha+\beta\times x=y
If it is observed that y \in (-8.51,23.20) given x=4
The question is to give intervals of \alpha, \beta, which satisfy y \in (-8.51,23.20) given x=4.
Is this problem identifiable? Can it be found the unique intervals for \alpha...
Say,
I'm a bookkeeper of a gamble of flip coin. The price for each trial is 0.5, i.e. if there is a head I pay gambler 0.5, otherwise I get 0.5 from the gambler. There are only 10 flips or trials in the game, so that each gamble only can play 10 trials. I know to choose the 0.5 as the fair...
Hi all,
I want to learn Game-Theoretic Probability. I have found few examples of computing conditional probability by game theoretic approach.
Is there and good readable tutorial could show help me to learn this topic and conformal predictions?
Let's recover this lost philosophy of...
\sum_{m=1}^N(\frac{1}{m^4}-\frac{1}{m^6})
My math on sum series is very rusty, can anyone show me show this sum converges?
It is not geometric series, right?
Suddenly found out it is needed to show Kolmogorov SLLN of some random varianble.
Thanks in advance
The compressed R packages have file extension .tar, they are called tar balls.
If you open the tar balls, you can see all sources codes are ASCII text files.
Variables x, y, z, in algebra, are place holders.
q(y,x)=normal(0,1) means y=0 x=1
Algebra is a incomplete story of placeholders. Be careful where you can plugin the values.
Copula is just a joint probability distribution. The beauty is that copula models correlation. The downside is it is difficult to formulate different couplas. I like baysian network modelling of joint distributions. Baysian network handles more variables, not only bivariates; the downside is...