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Joint distribution for Z = g ( X , Y ) = | | X | - Y | And W = h ( X , Y ) = | X Y |

% file jdemo3.m data for joint simple distribution X = [-4 -2 0 1 3]; Y = [0 1 2 4]; P = [0.0132 0.0198 0.0297 0.0209 0.0264;0.0372 0.0558 0.0837 0.0589 0.0744; 0.0516 0.0774 0.1161 0.0817 0.1032;0.0180 0.0270 0.0405 0.0285 0.0360];jdemo3 % Call for data jointzw % Call for m-programEnter joint prob for (X,Y): P Enter values for X: XEnter values for Y: Y Enter expression for g(t,u): abs(abs(t)-u)Enter expression for h(t,u): abs(t.*u) Use array operations on Z, W, PZ, PW, v, w, PZWdisp(PZW) 0.0132 0 0 0 00 0.0264 0 0 0 0 0 0.0570 0 00 0.0744 0 0 0 0.0558 0 0 0.0725 00 0 0.1032 0 0 0 0.1363 0 0 00.0817 0 0 0 0 0.0405 0.1446 0.1107 0.0360 0.0477EZ = total(v.*PZW) EZ = 1.4398ez = Z*PZ' % Alternate, using marginal dbnez = 1.4398 EW = total(w.*PZW)EW = 2.6075 ew = W*PW' % Alternate, using marginal dbnew = 2.6075 M = v>w; % P(Z>W) PM = total(M.*PZW)PM = 0.3390
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At noted in the previous section, if { X , Y } is an independent pair and Z = g ( X ) ,

W = h ( Y ) , then the pair { Z , W } is independent. However, if Z = g ( X , Y ) and

W = h ( X , Y ) , then in general the pair { Z , W } is not independent. We may illustrate this with the aid of the m-procedure jointzw

Functions of independent random variables

jdemo3 itestEnter matrix of joint probabilities P The pair {X,Y} is independent % The pair {X,Y} is independentjointzw Enter joint prob for (X,Y): PEnter values for X: X Enter values for Y: YEnter expression for g(t,u): t.^2 - 3*t % Z = g(X) Enter expression for h(t,u): abs(u) + 3 % W = h(Y)Use array operations on Z, W, PZ, PW, v, w, PZW itestEnter matrix of joint probabilities PZW The pair {X,Y} is independent % The pair {g(X),h(Y)} is independentjdemo3 % Refresh data jointzwEnter joint prob for (X,Y): P Enter values for X: XEnter values for Y: Y Enter expression for g(t,u): t+u % Z = g(X,Y)Enter expression for h(t,u): t.*u % W = h(X,Y) Use array operations on Z, W, PZ, PW, v, w, PZW itest Enter matrix of joint probabilities PZWThe pair {X,Y} is NOT independent % The pair {g(X,Y),h(X,Y)} is not indep To see where the product rule fails, call for D % Fails for all pairs
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Absolutely continuous case: analysis and approximation

As in the analysis Joint Distributions , we may set up a simple approximation to the joint distribution and proceed as for simple random variables. In this section, we solve severalexamples analytically, then obtain simple approximations.

Distribution for a product

Suppose the pair { X , Y } has joint density f X Y . Let Z = X Y . Determine Q v such that P ( Z v ) = P ( X , Y ) Q v .

This graph consist of an area bounded by two curves. One curve exist in the top right section and bottom left portion of a graph. The bottom left curve is labeled u=v/t v>0. The upper right portion is labeled u=v/t v<0. The bounded area is labeled Q_v. This graph consist of an area bounded by two curves. One curve exist in the top right section and bottom left portion of a graph. The bottom left curve is labeled u=v/t v>0. The upper right portion is labeled u=v/t v<0. The bounded area is labeled Q_v.
Region Q v for product X Y , v 0 .

SOLUTION (see [link] )

Q v = { ( t , u ) : t u v } = { ( t , u ) : t > 0 , u v / t } { ( t , u ) : t < 0 , u v / t } }
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Source:  OpenStax, Applied probability. OpenStax CNX. Aug 31, 2009 Download for free at http://cnx.org/content/col10708/1.6
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