MATH 4280 Lecture : MATH4280_2012Lec1.pdf
4 Dec 2013
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Thus xd := (x d |x > d ). Thus xd := (x d |x > d ). the expected value of x k d. Thus xd := (x d |x > d ). the expected value of x k expectancy), k n d (e[xd ] is the complete life. Let x f and e[x ] denote the expectation of x , then. The excess of loss r. v. is xd := x d given that x > d, where. Thus xd := (x d |x > d ). the expected value of x k expectancy), k n is thus d (e[xd ] is the complete life. P[x > d ]z d (x d )kdf (x), If x is a discrete r. v. , then the expected value of x k d is. E[x k d ] = e[(x d )k |x > d ] = P[x > d ] xxj >d (xj d )k p(xj ).
