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Suppose that Xi,i=1,2,3, are independent Poisson random variables with respective means i,i=1,2,3. Let X=X1+X2and Y=X2+X3. The random vector X,Y is said to have a bivariate Poisson distribution.
(a) Find E[X]and E[Y].
(b) Find Cov(X,Y).
(c) Find the joint probability mass function P{X=i, Y=j}.

Short Answer

Expert verified

(a)Therefore, the required E[X]and E[Y]isE[X]=1+2;E[Y]=2+3

(b)Therefore, the required Cov(X,Y)=2

(c)Therefore,

P{X=i,Y=j}=k=0min(i,j)e-11i-k(i-k)!e-13j-k(j-k)!2kk!e-2

Step by step solution

01

Concept Introduction(part a)

The question asks to find E[X]. It is given that Xi,i=1,2,3, are independent Poisson random variables with respective means i, for all i=1,2,3.

By using the common property of expectation values, one has that:
E[X]=EX1+X2

=EX1+EX2

=1+2

02

Step2:Explanation(part a)

Similarly, for Y :
E[Y]=EX2+X3

=EX2+EX3

Therefore, the required E[X]and E[Y]is E[X]=1+2;E[Y]=2+3

03

Step3:Final Answer

Therefore, the required E[X]and E[Y]is E[X]=1+2;E[Y]=2+3

04

:Concept Introduction(part b)

Compute, Cov(X,Y)

05

:Explanation(part b)

Compute, Cov(X,Y)
Cov(X,Y)=CovX1+X2,X2+X3

=CovX2,X2


06

Explanation(part b)

Cov(X,Y)=2From the property of variance and covariance, CovX2,X2=VarX2

Thus,
Cov(X,Y)=CovX2,X2

Cov(X,Y)=VarX2

Cov(X,Y)=2



07

Final Answer(part b)

Therefore, the required Cov(X,Y)=2

08

Concept Introduction(part c)

Find the joint probability mass function P{X=i,Y=j}.

09

Explanation(part c)

Find the joint probability mass function P{X=i,Y=j}.
In order to find the joint probability function, one conditions on X2, and use the property of Poisson random variables.
Accordingly:

P{X=i,Y=j}=kPX=i,Y=jX2=kPX2=k

=kPX1=i-k,X3=j-kX2=ke-22kk!

10

:Explanation(part c)

Since
X=X1+X2and Y=X2+X3Y=X2+X3

=kPX1=i-k,X3=j-ke-22kk!

=kPX1=i-kPX3=j-ke-22kk!

11

:Explanation(part c)

It is given that Xi,i=1,2,3 are independent Poisson random variables, hence using the property of Poisson random variables:

PX1=i-k=e-11i-k(i-k)!

PX3=j-k=e-33j-k(j-k)!

12

Step12:Final Answer(part c)

Therefore,
P{X=i,Y=j}=k=0min(i,j)e-11i-k(i-k)!e-33j-k(j-k)!2kk!e-2

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Most popular questions from this chapter

There are n items in a box labeled H and m in a box labeled T. A coin that comes up heads with probability p and tails with probability 1 鈭 p is flipped. Each time it comes up heads, an item is removed from the H box, and each time it comes up tails, an item is removed from the T box. (If a box is empty and its outcome occurs, then no items are removed.) Find the expected number of coin flips needed for both boxes to become empty. Hint: Condition on the number of heads in the first n + m flips.

A bottle initially contains m large pills and n small pills. Each day, a patient randomly chooses one of the pills. If a small pill is chosen, then that pill is eaten. If a large pill is chosen, then the pill is broken in two; one part is returned to the bottle (and is now considered a small pill) and the other part is then eaten.

(a) Let X denote the number of small pills in the bottle after the last large pill has been chosen and its smaller half returned. Find E[X].

Hint: De铿乶e n + m indicator variables, one for each of the small pills initially present and one for each of the small pills created when a large one is split in two. Now use the argument of Example 2m.

(b) Let Y denote the day on which the last large pills chosen. Find E[Y].

Hint: What is the relationship between X and Y?

7.4. If X and Y have joint density function fX,Y(x,y)={1/y,if0<y<1,0<x<y0,otherwisefind

(a) E[X Y]

(b) E[X]

(c) E[Y]

A certain region is inhabited by r distinct types of a certain species of insect. Each insect caught will, independently of the types of the previous catches, be of type i with probability

Pi,i=1,,r1rPi=1

(a) Compute the mean number of insects that are caught before the 铿乺st type 1catch.

(b) Compute the mean number of types of insects that are caught before the 铿乺st type1 catch.

Consider a population consisting of individuals able to produce offspring of the same kind. Suppose that by the end of its lifetime, each individual will have produced j new offspring with probability Pj, j0, independently of the number produced by any other individual. The number of individuals initially present, denoted by X0, is called the size of the zeroth generation. All offspring of the zeroth generation constitute the first generation, and their number is denoted by X1. In general, let Xn denote the size of the nth generation. Let =j=0jPjand 2=j=0(j)2Pj denote, respectively, the mean and the variance of the number of offspring produced by a single individual. Suppose that X0 = 1鈥 that is, initially there is a single individual in the population

(a) Show that EXn=EXn1.

(b) Use part (a) to conclude that EXn=n

(c) Show that VarXn=2n1+2VarXn1

(d) Use part (c) to conclude that

VarXn=2n1n11鈥呪赌呪赌呪赌if1n2鈥呪赌呪赌呪赌if=1

The model just described is known as a branching process, and an important question for a population that evolves along such lines is the probability that the population will eventually die out. Let 蟺 denote this probability when the population starts with a single individual. That is,

=P{population eventually dies outX0=1

(e) Argue that 蟺 satisfies

=j=0Pjj

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