Given Cont.Joint PDF function find Covariance MATRIX

circuitman
Messages
1
Reaction score
0
Hello Buddies,

I need to calculate "covariance matrix" of the given joint PDF function.

Joint PDF is fx(x1,x2,x3)=2/3(x1+x2+x3)

over S (x1,x2,x3), 0<xi<1, i=1,2,3

How can I calculte the Covariance Matrix?

Thanks
 
Physics news on Phys.org
There's a lot of symmetry to exploit here. Here is an outline of the brute force approach.

Step 1: Find E(X_1). What will that tell you about the other 2 means.

Step 2: Find E(X_1^2), from this and Step 1 you can get \sigma_{X_1}^2 (again - what about the other two?)

Step 3: Now get the covariances between X_1 and X_2 and X_1 and X_3.

Once you have these things you can assemble the covariance matrix.

By the way: I'm assuming you meant that

<br /> f(x_1, x_2, x_3) = \frac 2 3 \left(x_1 + x_2 + x_3\right), \quad 0 &lt; x_1, x_2, x_3 &lt; 1<br />

rather than something like

<br /> \frac{2}{3(x_1 + x_2 + x_3)}, \quad 0&lt;x_1, x_2, x_3 &lt; 1<br />

since the second version isn't a density function.
 
Namaste & G'day Postulate: A strongly-knit team wins on average over a less knit one Fundamentals: - Two teams face off with 4 players each - A polo team consists of players that each have assigned to them a measure of their ability (called a "Handicap" - 10 is highest, -2 lowest) I attempted to measure close-knitness of a team in terms of standard deviation (SD) of handicaps of the players. Failure: It turns out that, more often than, a team with a higher SD wins. In my language, that...
Hi all, I've been a roulette player for more than 10 years (although I took time off here and there) and it's only now that I'm trying to understand the physics of the game. Basically my strategy in roulette is to divide the wheel roughly into two halves (let's call them A and B). My theory is that in roulette there will invariably be variance. In other words, if A comes up 5 times in a row, B will be due to come up soon. However I have been proven wrong many times, and I have seen some...
Back
Top