Let {an} be a sequence of positive numbers satisfying En=1 an = 1 and let {Pn} be a sequence of probability measures on a common measurable space. Define P =E1 an Pn. (a) Show that P is a probability measure. (b) Show that Pn

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Let {an} be a sequence of positive numbers satisfying E1 an = 1
and let {Pn} be a sequence of probability measures on a common
measurable space. Define P = En=1 an Pn.
(a) Show that P is a probability measure.
(b) Show that Pn «v for all n and a measure v if and only if P <v
and, when P<v and v is o-finite,
(c) Derive the Lebesgue p.d.f. of P when Pn is the gamma distribution
T(a, n-1) (Table 1.2) with a > 1 and an is proportional to n-a.
dPn
En=1 an dv
dP
"<<" denoted as absolutely continuity
Transcribed Image Text:Let {an} be a sequence of positive numbers satisfying E1 an = 1 and let {Pn} be a sequence of probability measures on a common measurable space. Define P = En=1 an Pn. (a) Show that P is a probability measure. (b) Show that Pn «v for all n and a measure v if and only if P <v and, when P<v and v is o-finite, (c) Derive the Lebesgue p.d.f. of P when Pn is the gamma distribution T(a, n-1) (Table 1.2) with a > 1 and an is proportional to n-a. dPn En=1 an dv dP "<<" denoted as absolutely continuity
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