Transcription of Chapter 4. Multivariate Distributions
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Chapter 4. Multivariate Distributions
1 Chapter 4. Multivariate Distributions Joint ( ) Independent Random Variables Covariance and Correlation Coefficient Expectation and Covariance Matrix Multivariate (Normal) Distributions Matlab Codes for Multivariate (Normal) Distributions Some Practical Examples The Joint probability Mass Functions and LetXandYbe two discrete random variables and letRbe the corresponding space ofXandY. The joint ofX=xandY=y, denoted byf(x, y)=P(X=x, Y=y),has the following properties:(a)0 f(x, y) 1for(x, y) R.(b) (x,y) Rf(x, y)=1,(c)P(A)= (x,y) Af(x, y), whereA R.
1 Chapter 4. Multivariate Distributions ♣ Joint p.m.f. (p.d.f.) ♣ Independent Random Variables ♣ Covariance and Correlation Coefficient ♣ Expectation and Covariance Matrix ♣ Multivariate (Normal) Distributions ♣ Matlab Codes for Multivariate (Normal) Distributions ♣ Some Practical Examples The Joint Probability Mass Functions and p.d.f. • Let X and Y be two discrete random ...
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