Let x = (x1, . . . , xn1) and censored observations (xn1 +1, . . .

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Let x = (x1, . . . , xn1) and censored observations (xn1 +1, . . . ,xn) (that is, ith experiment, if I > n1, the survival time is at least yi). Let the new complete censored data yi be such that
Let x = (x1, . . . , xn1) and

Let the mean survival time be θ and the probability density of y be

Let x = (x1, . . . , xn1) and

and let the survival function be defined as the probability that an individual survives beyond time y, that is, S(y) = P(Y > y). Thus,

Let x = (x1, . . . , xn1) and

(a) Obtain the MLE, θ-capM:
(b) Obtain an EM algorithm.

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Mathematical Statistics With Applications In R

ISBN: 9780124171138

2nd Edition

Authors: Chris P. Tsokos, K.M. Ramachandran

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