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Can I get a detailed answer for this question.Suppose {u_(1),u_(2),u_(3)...} is a sequence of independent observations generated from UUNIF(0,1) . Define x_(1)=-theta ln(1-u_(1)),x_(2)=-theta ln(1-u_(2)),x_(3)=-theta ln(1-u_(3)),dots

Can I get a detailed answer for this question.Suppose

{u_(1),u_(2),u_(3)...}

is a sequence of independent observations generated from

UUNIF(0,1)

. Define\

x_(1)=-\\\\theta ln(1-u_(1)),x_(2)=-\\\\theta ln(1-u_(2)),x_(3)=-\\\\theta ln(1-u_(3)),dots\ y_(1)=-\\\\theta lnu_(1),y_(2)=-\\\\theta lnu_(2),y_(3)=-\\\\theta lnu_(3),dots

\ Verify that both

{x_(1),x_(2),..}

and

{y_(1),y_(2),..}

are sequences of independent observations generated from the same\ distribution

F

, and determine

F

.

image text in transcribed
x1=ln(1u1),x2=ln(1u2),x3=ln(1u3),y1=lnu1,y2=lnu2,y3=lnu3, Verify that both {x1,x2,} and {y1,y2,} are sequences of independent observations generated from the same distribution F, and determine F

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