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slide-1
SLIDE 1

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

▼❛❣♥✉s ❘❛ttr❛② ❙❝❤♦♦❧ ♦❢ ❈♦♠♣✉t❡r ❙❝✐❡♥❝❡✱ ❯♥✐✈❡rs✐t② ♦❢ ▼❛♥❝❤❡st❡r ❇❛②❡s✐❛♥ ❘❡s❡❛r❝❤ ❑✐t❝❤❡♥✱ ❆♠❜❧❡s✐❞❡✱ ❙❡♣t❡♠❜❡r ✻t❤ ✷✵✵✽

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-2
SLIDE 2

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❚❛❧❦ ❖✉t❧✐♥❡

◮ ❇r✐❡❢ ♦✈❡r✈✐❡✇ ♦❢ ♣♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ◮ ❊①❛♠♣❧❡ ❛♣♣❧✐❝❛t✐♦♥✿ s♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❢♦r

♥❡t✇♦r❦ ✐♥❢❡r❡♥❝❡

◮ ❚❤❡♦r② ❢♦r ❛✈❡r❛❣❡✲❝❛s❡ ♣❡r❢♦r♠❛♥❝❡ ✇✐t❤ ♠✐①t✉r❡ ♣r✐♦r ◮ ❚❤❡♦r② ❛♥❞ ▼❈▼❈ r❡s✉❧ts ❢♦r ❞✐✛❡r❡♥t ❞❛t❛ ❞✐str✐❜✉t✐♦♥s ◮ ❈♦♠♣❛r✐s♦♥ ✇✐t❤ ▲✶ ♣r✐♦r ◮ ❉✐s❝✉ss✐♦♥

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

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SLIDE 3

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs

❙♣❛rs✐t② ♣r✐♦rs t❡♥❞ t♦ ❜❡ ❝♦♥✈❡♥✐❡♥t r❛t❤❡r t❤❛♥ r❡❛❧✐st✐❝✱ ❡✳❣✳ ▲✶ ♣ ✇✐ ✷ ❡

✇✐

❆❘❉ ♣ ✇✐ ✇✐ ✵

✶ ✐

▼✐①t✉r❡ ♣ ✇✐ ✶ ❈ ✇✐ ❈ ✇✐ ✵

■s ✐t ❖❑ t♦ ♥♦t ✇♦rr② ❛❜♦✉t ✇❤❡t❤❡r t❤❡s❡ ❛❝t✉❛❧❧② ✜t t❤❡ ❞❛t❛❄

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-4
SLIDE 4

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs

❙♣❛rs✐t② ♣r✐♦rs t❡♥❞ t♦ ❜❡ ❝♦♥✈❡♥✐❡♥t r❛t❤❡r t❤❛♥ r❡❛❧✐st✐❝✱ ❡✳❣✳

◮ ▲✶

♣(✇✐) = λ ✷ ❡−λ|✇✐| ❆❘❉ ♣ ✇✐ ✇✐ ✵

✶ ✐

▼✐①t✉r❡ ♣ ✇✐ ✶ ❈ ✇✐ ❈ ✇✐ ✵

■s ✐t ❖❑ t♦ ♥♦t ✇♦rr② ❛❜♦✉t ✇❤❡t❤❡r t❤❡s❡ ❛❝t✉❛❧❧② ✜t t❤❡ ❞❛t❛❄

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-5
SLIDE 5

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs

❙♣❛rs✐t② ♣r✐♦rs t❡♥❞ t♦ ❜❡ ❝♦♥✈❡♥✐❡♥t r❛t❤❡r t❤❛♥ r❡❛❧✐st✐❝✱ ❡✳❣✳

◮ ▲✶

♣(✇✐) = λ ✷ ❡−λ|✇✐|

◮ ❆❘❉

♣(✇✐) = N(✇✐|✵, λ−✶

) ▼✐①t✉r❡ ♣ ✇✐ ✶ ❈ ✇✐ ❈ ✇✐ ✵

■s ✐t ❖❑ t♦ ♥♦t ✇♦rr② ❛❜♦✉t ✇❤❡t❤❡r t❤❡s❡ ❛❝t✉❛❧❧② ✜t t❤❡ ❞❛t❛❄

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-6
SLIDE 6

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs

❙♣❛rs✐t② ♣r✐♦rs t❡♥❞ t♦ ❜❡ ❝♦♥✈❡♥✐❡♥t r❛t❤❡r t❤❛♥ r❡❛❧✐st✐❝✱ ❡✳❣✳

◮ ▲✶

♣(✇✐) = λ ✷ ❡−λ|✇✐|

◮ ❆❘❉

♣(✇✐) = N(✇✐|✵, λ−✶

)

◮ ▼✐①t✉r❡

♣(✇✐) = (✶ − ❈)δ(✇✐) + ❈N(✇✐|✵, λ−✶) ■s ✐t ❖❑ t♦ ♥♦t ✇♦rr② ❛❜♦✉t ✇❤❡t❤❡r t❤❡s❡ ❛❝t✉❛❧❧② ✜t t❤❡ ❞❛t❛❄

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-7
SLIDE 7

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs

❙♣❛rs✐t② ♣r✐♦rs t❡♥❞ t♦ ❜❡ ❝♦♥✈❡♥✐❡♥t r❛t❤❡r t❤❛♥ r❡❛❧✐st✐❝✱ ❡✳❣✳

◮ ▲✶

♣(✇✐) = λ ✷ ❡−λ|✇✐|

◮ ❆❘❉

♣(✇✐) = N(✇✐|✵, λ−✶

)

◮ ▼✐①t✉r❡

♣(✇✐) = (✶ − ❈)δ(✇✐) + ❈N(✇✐|✵, λ−✶) ■s ✐t ❖❑ t♦ ♥♦t ✇♦rr② ❛❜♦✉t ✇❤❡t❤❡r t❤❡s❡ ❛❝t✉❛❧❧② ✜t t❤❡ ❞❛t❛❄

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-8
SLIDE 8

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❘❡❣✉❧❛t♦r② ♥❡t✇♦r❦ ✐♥❢❡r❡♥❝❡

  • ✐❜❜s s❛♠♣❧❡r

❊①❛♠♣❧❡ ❛♣♣❧✐❝❛t✐♦♥✿ ❢❛❝t♦r ❛♥❛❧②s✐s ❢♦r ♥❡t✇♦r❦ ✐♥❢❡r❡♥❝❡

❨ ∼ N(❲❩ + µ, Ψ) ❨ = [②✐♥] ❧♦❣✲❡①♣r❡ss✐♦♥ ♦❢ ❣❡♥❡ ✐ ✐♥ s❛♠♣❧❡ ♥ ❩ = [③❥♥] ❧♦❣✲❝♦♥❝❡♥tr❛t✐♦♥ ✭♦r ✧❛❝t✐✈✐t②✧✮ ♦❢ ❚❋ ❥ ✐♥ s❛♠♣❧❡ ♥ ❲ = [✇✐❥] ❢❛❝t♦r ❧♦❛❞✐♥❣ ✐s ✏❡✛❡❝t✑ ♦❢ ❚❋ ❥ ♦♥ ❣❡♥❡ ✐

◮ ▼♦❞❡❧ ❩ ❛s ❧❛t❡♥t ✈❛r✐❛❜❧❡✱ s✐♥❝❡ ♠❘◆❆ ❞❛t❛ ♠❛② ♥♦t ❝❛♣t✉r❡

❚❋ ♣r♦t❡✐♥ ❧❡✈❡❧✴❛❝t✐✈✐t②✱ ♦r ❚❋s t♦♦ ✇❡❛❦❧② ❡①♣r❡ss❡❞

◮ ❋♦r ❡✳❣✳ ②❡❛st ❲ r♦✉❣❤❧② ✻✵✵✵ × ✷✵✵ ◮ ❱❛r✐♦✉s ♠❡t❤♦❞s ❢♦r ✐♥❢❡rr✐♥❣ s♣❛rs❡ ❲ ❢r♦♠ ❨ ✭r❡✈✐❡✇❡❞ ❜②

P♦✉r♥❛r❛ ❛♥❞ ❲❡r♥✐s❝❤✱ ❇▼❈ ❇✐♦✐♥❢♦r♠❛t✐❝s ✷✵✵✼✮✳

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-9
SLIDE 9

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❘❡❣✉❧❛t♦r② ♥❡t✇♦r❦ ✐♥❢❡r❡♥❝❡

  • ✐❜❜s s❛♠♣❧❡r

❋❛❝t♦r ❛♥❛❧②s✐s ❢♦r ♥❡t✇♦r❦ ✐♥❢❡r❡♥❝❡

❨ ∼ N(❲❩ + µ, Ψ)

◮ ▼✐①t✉r❡ ♣r✐♦r ❧❡❛❞s t♦ tr❛❝t❛❜❧❡ ●✐❜❜s s❛♠♣❧❡r

♣(✇✐❥) = (✶ − ❈✐❥)δ(✇✐❥) + ❈✐❥N(✇✐❥|✵, λ−✶)

◮ ❍②♣❡r✲♣❛r❛♠❡t❡rs ❈✐❥ ∈ [✵, ✶] ❝❛♥ ❜❡ ♦❜t❛✐♥❡❞ ❢r♦♠ ❡✳❣✳

◮ ❈❤■P✲❝❤✐♣ ❞❛t❛ ◮ ❉◆❆ ♠♦t✐❢s ✭❙❛❜❛tt✐ ❛♥❞ ❏❛♠❡s✱ ❇✐♦✐♥❢♦r♠❛t✐❝s ✷✵✵✻✮

◮ ❖r ✇❡ ❝❛♥ ❡st✐♠❛t❡ ✭❣r♦✉♣❡❞✮ ❤②♣❡r✲♣❛r❛♠❡t❡rs ❜② ▼❈▼❈

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-10
SLIDE 10

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❘❡❣✉❧❛t♦r② ♥❡t✇♦r❦ ✐♥❢❡r❡♥❝❡

  • ✐❜❜s s❛♠♣❧❡r
  • ✐❜❜s s❛♠♣❧❡r

❲r✐t❡ ✇✐❥ = ①✐❥❜✐❥ ✇❤❡r❡ ①✐❥ ∈ {✵, ✶} ❛♥❞ ❜✐❥ ∼ N(✵, λ−✶) ①·❥ ∼ ♣(①·❥|❳ \ ①·❥, ❩, ❨) (✶) ❇ ∼ ♣(❇|❳, ❩, ❨) (✷) ❩ ∼ ♣(❩|❳, ❇, ❨) (✸) ■♥t❡❣r❛t❡ ♦✉t ❇ ❜❡❢♦r❡ s❛♠♣❧✐♥❣ ❳ ✭✷✱✸✮ ♠♦r❡ ❡✣❝✐❡♥t ✇❤❡♥ ❳ ✐s t②♣✐❝❛❧❧② s♣❛rs❡ ❈❛♥ ❛❧s♦ s❛♠♣❧❡ ❤②♣❡r✲♣❛r❛♠❡t❡rs ❈✐❥ ❛♥❞ ✐❢ r❡q✉✐r❡❞

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-11
SLIDE 11

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❘❡❣✉❧❛t♦r② ♥❡t✇♦r❦ ✐♥❢❡r❡♥❝❡

  • ✐❜❜s s❛♠♣❧❡r
  • ✐❜❜s s❛♠♣❧❡r

❲r✐t❡ ✇✐❥ = ①✐❥❜✐❥ ✇❤❡r❡ ①✐❥ ∈ {✵, ✶} ❛♥❞ ❜✐❥ ∼ N(✵, λ−✶) ①·❥ ∼ ♣(①·❥|❳ \ ①·❥, ❩, ❨) (✶) ❇ ∼ ♣(❇|❳, ❩, ❨) (✷) ❩ ∼ ♣(❩|❳, ❇, ❨) (✸)

◮ ■♥t❡❣r❛t❡ ♦✉t ❇ ❜❡❢♦r❡ s❛♠♣❧✐♥❣ ❳ ◮ ✭✷✱✸✮ ♠♦r❡ ❡✣❝✐❡♥t ✇❤❡♥ ❳ ✐s t②♣✐❝❛❧❧② s♣❛rs❡ ◮ ❈❛♥ ❛❧s♦ s❛♠♣❧❡ ❤②♣❡r✲♣❛r❛♠❡t❡rs ❈✐❥ ❛♥❞ λ ✐❢ r❡q✉✐r❡❞

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-12
SLIDE 12

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❢♦r s♣❛rs❡ ❇❛②❡s✐❛♥ P❈❆

② ♥ ∼ N(✵, σ✷■ + ✇✇ ❚) ♣(✇|❈, λ) =

  • ✐=✶
  • (✶ − ❈)δ(✇✐) + ❈N(✇✐|✵, λ−✶)
  • ❲❡ st✉❞② ❛✈❡r❛❣❡ ❜❡❤❛✈✐♦✉r ♦✈❡r ❞❛t❛s❡ts

❉ ② ✶ ② ✷ ② ▼ ♣r♦❞✉❝❡❞ ❜② ❛ t❡❛❝❤❡r ❞✐str✐❜✉t✐♦♥ ❚❤❡ t❡❛❝❤❡r ✐s ✐❞❡♥t✐❝❛❧ ❡①❝❡♣t ❢♦r ❛ ❞✐✛❡r❡♥t ❢❛❝t♦r✐③❡❞ ♣❛r❛♠❡t❡r ❞✐str✐❜✉t✐♦♥✳ ❲❡ ❝♦♥s✐❞❡r t✇♦ ❝❛s❡s✿ ✶ ❙❛♠❡ ❢♦r♠✿ ♣ ✇t

✶ ❈t ✇t

❈t ✇t

✐ ✵ ✶ t

✷ ❉✐✛❡r❡♥t ❢♦r♠✿ ♣ ✇t

✶ ❈t ✇t

❈t ✇t

✐ ✶ ✷ t

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-13
SLIDE 13

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❢♦r s♣❛rs❡ ❇❛②❡s✐❛♥ P❈❆

② ♥ ∼ N(✵, σ✷■ + ✇✇ ❚) ♣(✇|❈, λ) =

  • ✐=✶
  • (✶ − ❈)δ(✇✐) + ❈N(✇✐|✵, λ−✶)
  • ◮ ❲❡ st✉❞② ❛✈❡r❛❣❡ ❜❡❤❛✈✐♦✉r ♦✈❡r ❞❛t❛s❡ts

❉ = {② ✶, ② ✷, . . . , ② ▼} ♣r♦❞✉❝❡❞ ❜② ❛ t❡❛❝❤❡r ❞✐str✐❜✉t✐♦♥ ❚❤❡ t❡❛❝❤❡r ✐s ✐❞❡♥t✐❝❛❧ ❡①❝❡♣t ❢♦r ❛ ❞✐✛❡r❡♥t ❢❛❝t♦r✐③❡❞ ♣❛r❛♠❡t❡r ❞✐str✐❜✉t✐♦♥✳ ❲❡ ❝♦♥s✐❞❡r t✇♦ ❝❛s❡s✿ ✶ ❙❛♠❡ ❢♦r♠✿ ♣ ✇t

✶ ❈t ✇t

❈t ✇t

✐ ✵ ✶ t

✷ ❉✐✛❡r❡♥t ❢♦r♠✿ ♣ ✇t

✶ ❈t ✇t

❈t ✇t

✐ ✶ ✷ t

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-14
SLIDE 14

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❢♦r s♣❛rs❡ ❇❛②❡s✐❛♥ P❈❆

② ♥ ∼ N(✵, σ✷■ + ✇✇ ❚) ♣(✇|❈, λ) =

  • ✐=✶
  • (✶ − ❈)δ(✇✐) + ❈N(✇✐|✵, λ−✶)
  • ◮ ❲❡ st✉❞② ❛✈❡r❛❣❡ ❜❡❤❛✈✐♦✉r ♦✈❡r ❞❛t❛s❡ts

❉ = {② ✶, ② ✷, . . . , ② ▼} ♣r♦❞✉❝❡❞ ❜② ❛ t❡❛❝❤❡r ❞✐str✐❜✉t✐♦♥

◮ ❚❤❡ t❡❛❝❤❡r ✐s ✐❞❡♥t✐❝❛❧ ❡①❝❡♣t ❢♦r ❛ ❞✐✛❡r❡♥t ❢❛❝t♦r✐③❡❞

♣❛r❛♠❡t❡r ❞✐str✐❜✉t✐♦♥✳ ❲❡ ❝♦♥s✐❞❡r t✇♦ ❝❛s❡s✿ ✶ ❙❛♠❡ ❢♦r♠✿ ♣ ✇t

✶ ❈t ✇t

❈t ✇t

✐ ✵ ✶ t

✷ ❉✐✛❡r❡♥t ❢♦r♠✿ ♣ ✇t

✶ ❈t ✇t

❈t ✇t

✐ ✶ ✷ t

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-15
SLIDE 15

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❢♦r s♣❛rs❡ ❇❛②❡s✐❛♥ P❈❆

② ♥ ∼ N(✵, σ✷■ + ✇✇ ❚) ♣(✇|❈, λ) =

  • ✐=✶
  • (✶ − ❈)δ(✇✐) + ❈N(✇✐|✵, λ−✶)
  • ◮ ❲❡ st✉❞② ❛✈❡r❛❣❡ ❜❡❤❛✈✐♦✉r ♦✈❡r ❞❛t❛s❡ts

❉ = {② ✶, ② ✷, . . . , ② ▼} ♣r♦❞✉❝❡❞ ❜② ❛ t❡❛❝❤❡r ❞✐str✐❜✉t✐♦♥

◮ ❚❤❡ t❡❛❝❤❡r ✐s ✐❞❡♥t✐❝❛❧ ❡①❝❡♣t ❢♦r ❛ ❞✐✛❡r❡♥t ❢❛❝t♦r✐③❡❞

♣❛r❛♠❡t❡r ❞✐str✐❜✉t✐♦♥✳ ❲❡ ❝♦♥s✐❞❡r t✇♦ ❝❛s❡s✿ (✶) ❙❛♠❡ ❢♦r♠✿ ♣(✇t

✐ ) = (✶ − ❈t)δ(✇t ✐ ) + ❈tN(✇t ✐ |✵, λ−✶ t )

✷ ❉✐✛❡r❡♥t ❢♦r♠✿ ♣ ✇t

✶ ❈t ✇t

❈t ✇t

✐ ✶ ✷ t

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-16
SLIDE 16

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❢♦r s♣❛rs❡ ❇❛②❡s✐❛♥ P❈❆

② ♥ ∼ N(✵, σ✷■ + ✇✇ ❚) ♣(✇|❈, λ) =

  • ✐=✶
  • (✶ − ❈)δ(✇✐) + ❈N(✇✐|✵, λ−✶)
  • ◮ ❲❡ st✉❞② ❛✈❡r❛❣❡ ❜❡❤❛✈✐♦✉r ♦✈❡r ❞❛t❛s❡ts

❉ = {② ✶, ② ✷, . . . , ② ▼} ♣r♦❞✉❝❡❞ ❜② ❛ t❡❛❝❤❡r ❞✐str✐❜✉t✐♦♥

◮ ❚❤❡ t❡❛❝❤❡r ✐s ✐❞❡♥t✐❝❛❧ ❡①❝❡♣t ❢♦r ❛ ❞✐✛❡r❡♥t ❢❛❝t♦r✐③❡❞

♣❛r❛♠❡t❡r ❞✐str✐❜✉t✐♦♥✳ ❲❡ ❝♦♥s✐❞❡r t✇♦ ❝❛s❡s✿ (✶) ❙❛♠❡ ❢♦r♠✿ ♣(✇t

✐ ) = (✶ − ❈t)δ(✇t ✐ ) + ❈tN(✇t ✐ |✵, λ−✶ t )

(✷) ❉✐✛❡r❡♥t ❢♦r♠✿ ♣(✇t

✐ ) = (✶ − ❈t)δ(✇t ✐ ) + ❈tδ(✇t ✐ − λ−✶/✷ t

)

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-17
SLIDE 17

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❢♦r s♣❛rs❡ ❇❛②❡s✐❛♥ P❈❆

◮ ❈♦♠♣✉t❡ ♠❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ ❧♦❣ ♣(❉|❈, λ)❉ ✐♥ ❧✐♠✐t ◆ → ∞

✇✐t❤ α = ▼/◆ ❤❡❧❞ ❝♦♥st❛♥t ✉s✐♥❣ r❡♣❧✐❝❛ ♠❡t❤♦❞ ❈♦♠♣✉t❡ ❢✉♥❝t✐♦♥s ♦❢ t❤❡ ♠❡❛♥ ♣♦st❡r✐♦r ♣❛r❛♠❡t❡r ✇ ❉ ✇ ✇ ✇ t ✇ ✇ t ✇ ❧♦❣ ♣ ② ✇ ❈

② ✇ t

  • ♦♦❞ ❛❣r❡❡♠❡♥t ✇✐t❤ s✐♠✉❧❛t✐♦♥s ❢♦r ♠♦st r❡❧❡✈❛♥t ❝❛s❡ ♦❢

s♠❛❧❧ ✭s♦✲❝❛❧❧❡❞ ❧❛r❣❡ ◆ s♠❛❧❧ ♣ r❡❣✐♠❡✮

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-18
SLIDE 18

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❢♦r s♣❛rs❡ ❇❛②❡s✐❛♥ P❈❆

◮ ❈♦♠♣✉t❡ ♠❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ ❧♦❣ ♣(❉|❈, λ)❉ ✐♥ ❧✐♠✐t ◆ → ∞

✇✐t❤ α = ▼/◆ ❤❡❧❞ ❝♦♥st❛♥t ✉s✐♥❣ r❡♣❧✐❝❛ ♠❡t❤♦❞

◮ ❈♦♠♣✉t❡ ❢✉♥❝t✐♦♥s ♦❢ t❤❡ ♠❡❛♥ ♣♦st❡r✐♦r ♣❛r❛♠❡t❡r ✇ ∗(❉)

ρ(✇ ∗) = ✇ ∗ · ✇ t ||✇ ∗||||✇ t|| L(✇ ∗) = ❧♦❣ ♣(②|✇ ∗, ❈, λ)②|✇ t

  • ♦♦❞ ❛❣r❡❡♠❡♥t ✇✐t❤ s✐♠✉❧❛t✐♦♥s ❢♦r ♠♦st r❡❧❡✈❛♥t ❝❛s❡ ♦❢

s♠❛❧❧ ✭s♦✲❝❛❧❧❡❞ ❧❛r❣❡ ◆ s♠❛❧❧ ♣ r❡❣✐♠❡✮

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-19
SLIDE 19

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❢♦r s♣❛rs❡ ❇❛②❡s✐❛♥ P❈❆

◮ ❈♦♠♣✉t❡ ♠❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ ❧♦❣ ♣(❉|❈, λ)❉ ✐♥ ❧✐♠✐t ◆ → ∞

✇✐t❤ α = ▼/◆ ❤❡❧❞ ❝♦♥st❛♥t ✉s✐♥❣ r❡♣❧✐❝❛ ♠❡t❤♦❞

◮ ❈♦♠♣✉t❡ ❢✉♥❝t✐♦♥s ♦❢ t❤❡ ♠❡❛♥ ♣♦st❡r✐♦r ♣❛r❛♠❡t❡r ✇ ∗(❉)

ρ(✇ ∗) = ✇ ∗ · ✇ t ||✇ ∗||||✇ t|| L(✇ ∗) = ❧♦❣ ♣(②|✇ ∗, ❈, λ)②|✇ t

◮ ●♦♦❞ ❛❣r❡❡♠❡♥t ✇✐t❤ s✐♠✉❧❛t✐♦♥s ❢♦r ♠♦st r❡❧❡✈❛♥t ❝❛s❡ ♦❢

s♠❛❧❧ α ✭s♦✲❝❛❧❧❡❞ ❧❛r❣❡ ◆ s♠❛❧❧ ♣ r❡❣✐♠❡✮

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-20
SLIDE 20

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❢♦r s♣❛rs❡ ❇❛②❡s✐❛♥ P❈❆

◮ ❈♦♠♣✉t❡ ♠❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ ❧♦❣ ♣(❉|❈, λ)❉ ✐♥ ❧✐♠✐t ◆ → ∞

✇✐t❤ α = ▼/◆ ❤❡❧❞ ❝♦♥st❛♥t ✉s✐♥❣ r❡♣❧✐❝❛ ♠❡t❤♦❞

◮ ❈♦♠♣✉t❡ ❢✉♥❝t✐♦♥s ♦❢ t❤❡ ♠❡❛♥ ♣♦st❡r✐♦r ♣❛r❛♠❡t❡r ✇ ∗(❉)

ρ(✇ ∗) = ✇ ∗ · ✇ t ||✇ ∗||||✇ t|| L(✇ ∗) = ❧♦❣ ♣(②|✇ ∗, ❈, λ)②|✇ t

◮ ●♦♦❞ ❛❣r❡❡♠❡♥t ✇✐t❤ s✐♠✉❧❛t✐♦♥s ❢♦r ♠♦st r❡❧❡✈❛♥t ❝❛s❡ ♦❢

s♠❛❧❧ α ✭s♦✲❝❛❧❧❡❞ ❧❛r❣❡ ◆ s♠❛❧❧ ♣ r❡❣✐♠❡✮

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-21
SLIDE 21

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❢♦r s♣❛rs❡ ❇❛②❡s✐❛♥ P❈❆

◮ ❙✐♠✐❧❛r r❡♣❧✐❝❛ ❝❛❧❝✉❧❛t✐♦♥ t♦ ❯❞❛ ❛♥❞ ❑❛❜❛s❤✐♠❛ ✭❏✳ P❤②s✳

❙♦❝✳ ❏❛♣❛♥ ✼✹✱ ✷✵✵✺✮ ❩(❉) = ♣(❉|❈, λ) =

  • ❞✇♣(✇|❈, λ)

  • ♥=✶

♣(② ♥|✇) ✶ ◆ ❧♦❣ ❩(❉)❉,✇ t = ✶ ◆ ❧✐♠♥→✵ ∂ ∂♥❩ ♥(❉)❉,✇ t = α❧♦❣ ♣(②|✇ ∗(❉), ❈, λ)②,❉,✇ t + ❡♥tr♦♣✐❝ t❡r♠s ❆✈❡r❛❣❡ ❝❛s❡ ❜❡❝♦♠❡s t②♣✐❝❛❧ ❢♦r ❧❛r❣❡ ◆ ❞✉❡ t♦ s❡❧❢✲❛✈❡r❛❣✐♥❣

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-22
SLIDE 22

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❢♦r s♣❛rs❡ ❇❛②❡s✐❛♥ P❈❆

◮ ❙✐♠✐❧❛r r❡♣❧✐❝❛ ❝❛❧❝✉❧❛t✐♦♥ t♦ ❯❞❛ ❛♥❞ ❑❛❜❛s❤✐♠❛ ✭❏✳ P❤②s✳

❙♦❝✳ ❏❛♣❛♥ ✼✹✱ ✷✵✵✺✮ ❩(❉) = ♣(❉|❈, λ) =

  • ❞✇♣(✇|❈, λ)

  • ♥=✶

♣(② ♥|✇) ✶ ◆ ❧♦❣ ❩(❉)❉,✇ t = ✶ ◆ ❧✐♠♥→✵ ∂ ∂♥❩ ♥(❉)❉,✇ t = α❧♦❣ ♣(②|✇ ∗(❉), ❈, λ)②,❉,✇ t + ❡♥tr♦♣✐❝ t❡r♠s

◮ ❆✈❡r❛❣❡ ❝❛s❡ ❜❡❝♦♠❡s t②♣✐❝❛❧ ❢♦r ❧❛r❣❡ ◆ ❞✉❡ t♦ s❡❧❢✲❛✈❡r❛❣✐♥❣

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-23
SLIDE 23

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ✭❈❂✶✮

▲❡❛r♥✐♥❣ ❡①❤✐❜✐ts ♣❤❛s❡ tr❛♥s✐t✐♦♥s✱ ❡✳❣✳ ✭❢♦r α > ✶✮ ρ(✇∗) = θ(α − ❚ −✷) θ

  • α − λ

◆❚ α − ❚ −✷ α + ❚ −✶ ✇❤❡r❡ θ(①) ✐s t❤❡ st❡♣ ❢✉♥❝t✐♦♥ ❛♥❞ ❚ = ||✇t||✷

◆→∞ = ◆❈tλ−✶ t

. ❈♦♥s✐st❡♥t ✇✐t❤ r❡s✉❧t ❢♦r ❇❛②❡s✐❛♥ P❈❆ ✇✐t❤ s♣❤❡r✐❝❛❧ ♣r✐♦r ♣ ✇ ✇ ✶ ✭❘✐❡♠❛♥♥ ❡t ❛❧✳ ❏✳ P❤②s✳ ❆ ✶✾✾✻✮ ❖♥❧② ♥❡✇ ❢❡❛t✉r❡ ✐s ✶st✲♦r❞❡r tr❛♥s✐t✐♦♥ ✇✐t❤ ✐♥❝r❡❛s✐♥❣

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-24
SLIDE 24

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ✭❈❂✶✮

▲❡❛r♥✐♥❣ ❡①❤✐❜✐ts ♣❤❛s❡ tr❛♥s✐t✐♦♥s✱ ❡✳❣✳ ✭❢♦r α > ✶✮ ρ(✇∗) = θ(α − ❚ −✷) θ

  • α − λ

◆❚ α − ❚ −✷ α + ❚ −✶ ✇❤❡r❡ θ(①) ✐s t❤❡ st❡♣ ❢✉♥❝t✐♦♥ ❛♥❞ ❚ = ||✇t||✷

◆→∞ = ◆❈tλ−✶ t

.

◮ ❈♦♥s✐st❡♥t ✇✐t❤ r❡s✉❧t ❢♦r ❇❛②❡s✐❛♥ P❈❆ ✇✐t❤ s♣❤❡r✐❝❛❧ ♣r✐♦r

♣(✇) ∝ δ(||✇|| − ✶) ✭❘✐❡♠❛♥♥ ❡t ❛❧✳ ❏✳ P❤②s✳ ❆ ✶✾✾✻✮ ❖♥❧② ♥❡✇ ❢❡❛t✉r❡ ✐s ✶st✲♦r❞❡r tr❛♥s✐t✐♦♥ ✇✐t❤ ✐♥❝r❡❛s✐♥❣

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-25
SLIDE 25

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ✭❈❂✶✮

▲❡❛r♥✐♥❣ ❡①❤✐❜✐ts ♣❤❛s❡ tr❛♥s✐t✐♦♥s✱ ❡✳❣✳ ✭❢♦r α > ✶✮ ρ(✇∗) = θ(α − ❚ −✷) θ

  • α − λ

◆❚ α − ❚ −✷ α + ❚ −✶ ✇❤❡r❡ θ(①) ✐s t❤❡ st❡♣ ❢✉♥❝t✐♦♥ ❛♥❞ ❚ = ||✇t||✷

◆→∞ = ◆❈tλ−✶ t

.

◮ ❈♦♥s✐st❡♥t ✇✐t❤ r❡s✉❧t ❢♦r ❇❛②❡s✐❛♥ P❈❆ ✇✐t❤ s♣❤❡r✐❝❛❧ ♣r✐♦r

♣(✇) ∝ δ(||✇|| − ✶) ✭❘✐❡♠❛♥♥ ❡t ❛❧✳ ❏✳ P❤②s✳ ❆ ✶✾✾✻✮

◮ ❖♥❧② ♥❡✇ ❢❡❛t✉r❡ ✐s ✶st✲♦r❞❡r tr❛♥s✐t✐♦♥ ✇✐t❤ ✐♥❝r❡❛s✐♥❣ λ

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-26
SLIDE 26

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ✭❈❂✶✮

λt = ◆, ◆ = ✺✵✵✵, ▼ = ✷✵✵✵✵ (α = ✺)

2 4 6 8 10 0.2 0.4 0.6 0.8 1 λ/λt ρ(w*) Theory vs. MCMC averaged over 10 data sets

❍❡r❡ ✇❡ ✇✐❧❧ ♦♥❧② ❝♦♥s✐❞❡r ❧❡❛r♥✐♥❣ ❛✇❛② ❢r♦♠ ♣❤❛s❡ tr❛♥s✐t✐♦♥s

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-27
SLIDE 27

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ✭❈❂✶✮

λt = ◆, ◆ = ✺✵✵✵, ▼ = ✷✵✵✵✵ (α = ✺)

2 4 6 8 10 0.2 0.4 0.6 0.8 1 λ/λt ρ(w*) Theory vs. MCMC averaged over 10 data sets

❍❡r❡ ✇❡ ✇✐❧❧ ♦♥❧② ❝♦♥s✐❞❡r ❧❡❛r♥✐♥❣ ❛✇❛② ❢r♦♠ ♣❤❛s❡ tr❛♥s✐t✐♦♥s

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-28
SLIDE 28

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮

◮ ❲❡ ❝♦♥s✐❞❡r t✇♦ t②♣❡s ♦❢ ❞❛t❛ s❡t ❞✐str✐❜✉t✐♦♥✿

✶ ❙❛♠❡ ❢♦r♠ ❛s ♣r✐♦r✿ ♣ ✇t

✶ ❈t ✇t

❈t ✇t

✐ ✵ ✶ t

✷ ❉✐✛❡r❡♥t ❢♦r♠✿ ♣ ✇t

✶ ❈t ✇t

❈t ✇t

✐ ✶ ✷ t

❇♦t❤ ❣✐✈❡ ✐❞❡♥t✐❝❛❧ ♣❡r❢♦r♠❛♥❝❡ ❢♦r st❛♥❞❛r❞ P❈❆ ❇♦t❤ ❣✐✈❡ ✐❞❡♥t✐❝❛❧ ♣❡r❢♦r♠❛♥❝❡ ✐❢ s♣❛rs✐t② ✐s ❦♥♦✇♥

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-29
SLIDE 29

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮

◮ ❲❡ ❝♦♥s✐❞❡r t✇♦ t②♣❡s ♦❢ ❞❛t❛ s❡t ❞✐str✐❜✉t✐♦♥✿

(✶) ❙❛♠❡ ❢♦r♠ ❛s ♣r✐♦r✿ ♣(✇t

✐ ) = (✶ − ❈t)δ(✇t ✐ ) + ❈tN(✇t ✐ |✵, λ−✶ t )

✷ ❉✐✛❡r❡♥t ❢♦r♠✿ ♣ ✇t

✶ ❈t ✇t

❈t ✇t

✐ ✶ ✷ t

❇♦t❤ ❣✐✈❡ ✐❞❡♥t✐❝❛❧ ♣❡r❢♦r♠❛♥❝❡ ❢♦r st❛♥❞❛r❞ P❈❆ ❇♦t❤ ❣✐✈❡ ✐❞❡♥t✐❝❛❧ ♣❡r❢♦r♠❛♥❝❡ ✐❢ s♣❛rs✐t② ✐s ❦♥♦✇♥

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-30
SLIDE 30

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮

◮ ❲❡ ❝♦♥s✐❞❡r t✇♦ t②♣❡s ♦❢ ❞❛t❛ s❡t ❞✐str✐❜✉t✐♦♥✿

(✶) ❙❛♠❡ ❢♦r♠ ❛s ♣r✐♦r✿ ♣(✇t

✐ ) = (✶ − ❈t)δ(✇t ✐ ) + ❈tN(✇t ✐ |✵, λ−✶ t )

(✷) ❉✐✛❡r❡♥t ❢♦r♠✿ ♣(✇t

✐ ) = (✶ − ❈t)δ(✇t ✐ ) + ❈tδ(✇t ✐ − λ−✶/✷ t

) ❇♦t❤ ❣✐✈❡ ✐❞❡♥t✐❝❛❧ ♣❡r❢♦r♠❛♥❝❡ ❢♦r st❛♥❞❛r❞ P❈❆ ❇♦t❤ ❣✐✈❡ ✐❞❡♥t✐❝❛❧ ♣❡r❢♦r♠❛♥❝❡ ✐❢ s♣❛rs✐t② ✐s ❦♥♦✇♥

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-31
SLIDE 31

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮

◮ ❲❡ ❝♦♥s✐❞❡r t✇♦ t②♣❡s ♦❢ ❞❛t❛ s❡t ❞✐str✐❜✉t✐♦♥✿

(✶) ❙❛♠❡ ❢♦r♠ ❛s ♣r✐♦r✿ ♣(✇t

✐ ) = (✶ − ❈t)δ(✇t ✐ ) + ❈tN(✇t ✐ |✵, λ−✶ t )

(✷) ❉✐✛❡r❡♥t ❢♦r♠✿ ♣(✇t

✐ ) = (✶ − ❈t)δ(✇t ✐ ) + ❈tδ(✇t ✐ − λ−✶/✷ t

)

◮ ❇♦t❤ ❣✐✈❡ ✐❞❡♥t✐❝❛❧ ♣❡r❢♦r♠❛♥❝❡ ❢♦r st❛♥❞❛r❞ P❈❆

❇♦t❤ ❣✐✈❡ ✐❞❡♥t✐❝❛❧ ♣❡r❢♦r♠❛♥❝❡ ✐❢ s♣❛rs✐t② ✐s ❦♥♦✇♥

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-32
SLIDE 32

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮

◮ ❲❡ ❝♦♥s✐❞❡r t✇♦ t②♣❡s ♦❢ ❞❛t❛ s❡t ❞✐str✐❜✉t✐♦♥✿

(✶) ❙❛♠❡ ❢♦r♠ ❛s ♣r✐♦r✿ ♣(✇t

✐ ) = (✶ − ❈t)δ(✇t ✐ ) + ❈tN(✇t ✐ |✵, λ−✶ t )

(✷) ❉✐✛❡r❡♥t ❢♦r♠✿ ♣(✇t

✐ ) = (✶ − ❈t)δ(✇t ✐ ) + ❈tδ(✇t ✐ − λ−✶/✷ t

)

◮ ❇♦t❤ ❣✐✈❡ ✐❞❡♥t✐❝❛❧ ♣❡r❢♦r♠❛♥❝❡ ❢♦r st❛♥❞❛r❞ P❈❆ ◮ ❇♦t❤ ❣✐✈❡ ✐❞❡♥t✐❝❛❧ ♣❡r❢♦r♠❛♥❝❡ ✐❢ s♣❛rs✐t② ✐s ❦♥♦✇♥

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-33
SLIDE 33

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❘❡s✉❧ts ❢♦r ❞❛t❛ ❞✐str✐❜✉t✐♦♥ ✭✶✮✿ ρ(✇ ∗) ❛♥❞ L(✇ ∗)

♣(✇t

✐ ) = (✶ − ❈t)δ(✇t ✐ ) + ❈tN(✇t ✐ |✵, λ−✶ t )

❈t = ✵.✷, λ = λt = ◆/✶✵✵, ▼ = ✷✵✵, ◆ = ▼/α

0.2 0.4 0.6 0.8 1 0.4 0.5 0.6 0.7 0.8 0.9 1 C ρ(w*) Theory versus MCMC results for single dataset α=0.15 α=0.1 α=0.05 α=0.02 0.2 0.4 0.6 0.8 1 1 2 3 4 5 6 7 8 C L(w*) Theory versus MCMC results for single dataset α=0.15 α=0.1 α=0.05 α=0.02

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-34
SLIDE 34

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❘❡s✉❧ts ❢♦r ❞❛t❛ ❞✐str✐❜✉t✐♦♥ ✭✶✮✿ ρ(✇ ∗) ❛♥❞ L(✇ ∗)

♣(✇t

✐ ) = (✶ − ❈t)δ(✇t ✐ ) + ❈tN(✇t ✐ |✵, λ−✶ t )

❈t = ✵.✷, λ = λt = ◆/✶✵✵, ▼ = ✷✵✵, ◆ = ▼/α

0.2 0.4 0.6 0.8 1 0.4 0.5 0.6 0.7 0.8 0.9 1 C ρ(w*) Theory versus MCMC averaged over 10 datasets α=0.15 α=0.1 α=0.05 α=0.02 0.2 0.4 0.6 0.8 1 1 2 3 4 5 6 7 8 C L(w*) Theory versus MCMC averaged over 10 datasets α=0.15 α=0.1 α=0.05 α=0.02

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-35
SLIDE 35

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❘❡s✉❧ts ❢♦r ❞❛t❛ ❞✐str✐❜✉t✐♦♥ ✭✶✮✿ ρ(✇ ∗) ❛♥❞ L(✇ ∗)

❈t = ✵.✷, λt = ✷✵, ▼ = ✷✵✵, ◆ = ✷✵✵✵ (α = ✵.✶)

C λ/λt ρ(w*) 0.1 0.2 0.3 0.4 0.5 0.6 1 2 3 4 5 6 7 8 C λ/λt L(w*) 0.1 0.2 0.3 0.4 0.5 0.6 1 2 3 4 5 6 7 8 ❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-36
SLIDE 36

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❘❡s✉❧ts ❢♦r ❞❛t❛ ❞✐str✐❜✉t✐♦♥ ✭✶✮✿ ♣(❉|❈, λ)

❈t = ✵.✷, λt = ✷✵, ▼ = ✷✵✵, ◆ = ✷✵✵✵ (α = ✵.✶)

C λ/λt Theory for log p(D|C,λ) 0.1 0.15 0.2 0.25 0.3 0.5 1 1.5 2 C λ/λt MCMC for p(C,λ|D) averaged over 20 data sets 0.1 0.15 0.2 0.25 0.3 0.5 1 1.5 2 ❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-37
SLIDE 37

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❘❡s✉❧ts ❢♦r ❞❛t❛ ❞✐str✐❜✉t✐♦♥ ✭✷✮✿ ρ(✇ ∗)

♣(✇t

✐ ) = (✶ − ❈t)δ(✇t ✐ ) + ❈tδ(✇t ✐ − λ−✶/✷ t

) ❈t = ✵.✷, λ = λt = ◆/✶✵✵, ▼ = ✷✵✵, ◆ = ▼/α

0.2 0.4 0.6 0.8 1 0.4 0.5 0.6 0.7 0.8 0.9 1 C ρ(w*) Delta−mixture versus Gaussian−mixture theory α=0.2 α=0.15 α=0.1 α=0.05 0.2 0.4 0.6 0.8 1 0.4 0.5 0.6 0.7 0.8 0.9 1 C ρ(w*) Theory versus MCMC averaged over 10 datasets α=0.2 α=0.15 α=0.1 α=0.05

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-38
SLIDE 38

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❘❡s✉❧ts ❢♦r ❞❛t❛ ❞✐str✐❜✉t✐♦♥ ✭✷✮✿ ρ(✇ ∗) ❛♥❞ L(✇ ∗)

❈t = ✵.✷, λt = ✶✵, ▼ = ✷✵✵, ◆ = ✶✵✵✵ (α = ✵.✷)

C λ/λt ρ(w*) 0.1 0.2 0.3 0.4 0.5 0.6 1 2 3 4 5 6 7 8 C λ/λt L(w*) 0.1 0.2 0.3 0.4 0.5 0.6 1 2 3 4 5 6 7 8 ❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-39
SLIDE 39

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❘❡s✉❧ts ❢♦r ❞❛t❛ ❞✐str✐❜✉t✐♦♥ ✭✷✮✿ ♣(❉|❈, λ)

❈t = ✵.✷, λt = ✶✵, ▼ = ✷✵✵, ◆ = ✶✵✵✵ (α = ✵.✷)

C λ/λt Theory for log p(D|C,λ) 0.1 0.2 0.3 0.4 0.5 0.6 0.5 1 1.5 2 2.5 3 3.5 4 C λ/λt MCMC for p(C,λ|D) averaged over 20 data sets 0.1 0.2 0.3 0.4 0.5 0.6 0.5 1 1.5 2 2.5 3 3.5 4 ❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-40
SLIDE 40

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❖t❤❡r ♣r✐♦rs❄

◮ ■s t❤✐s ♣r♦❜❧❡♠ s♣❡❝✐✜❝ t♦ t❤❡ ♠✐①t✉r❡ ♣r✐♦r❄

❈♦♥s✐❞❡r t❤❡ ▲✶ ♣r✐♦r ✭✇✐t❤ ❛♥ ❛❞❞✐t✐♦♥❛❧ ▲✷ t❡r♠✮✱ ♣ ✇✐ ❡

✷✇✷ ✐ ✷ ✶ ✇✐

❉❛t❛ ❞✐str✐❜✉t✐♦♥ ✭✷✮ ♣ ✇t

✶ ❈t ✇t

❈t ✇t

✐ ✶ ✷ t

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-41
SLIDE 41

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❖t❤❡r ♣r✐♦rs❄

◮ ■s t❤✐s ♣r♦❜❧❡♠ s♣❡❝✐✜❝ t♦ t❤❡ ♠✐①t✉r❡ ♣r✐♦r❄ ◮ ❈♦♥s✐❞❡r t❤❡ ▲✶ ♣r✐♦r ✭✇✐t❤ ❛♥ ❛❞❞✐t✐♦♥❛❧ ▲✷ t❡r♠✮✱

♣(✇✐) ∝ ❡−

λ✷✇✷ ✐ ✷

−λ✶|✇✐|

❉❛t❛ ❞✐str✐❜✉t✐♦♥ ✭✷✮ ♣ ✇t

✶ ❈t ✇t

❈t ✇t

✐ ✶ ✷ t

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-42
SLIDE 42

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

❖t❤❡r ♣r✐♦rs❄

◮ ■s t❤✐s ♣r♦❜❧❡♠ s♣❡❝✐✜❝ t♦ t❤❡ ♠✐①t✉r❡ ♣r✐♦r❄ ◮ ❈♦♥s✐❞❡r t❤❡ ▲✶ ♣r✐♦r ✭✇✐t❤ ❛♥ ❛❞❞✐t✐♦♥❛❧ ▲✷ t❡r♠✮✱

♣(✇✐) ∝ ❡−

λ✷✇✷ ✐ ✷

−λ✶|✇✐| ◮ ❉❛t❛ ❞✐str✐❜✉t✐♦♥ ✭✷✮

♣(✇t

✐ ) = (✶ − ❈t)δ(✇t ✐ ) + ❈tδ(✇t ✐ − λ−✶/✷ t

)

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-43
SLIDE 43

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

▲✶ ♣r✐♦r r❡s✉❧ts✿ ρ(✇ ∗)

❈t = ✵.✷, λt = ◆/✶✵✵, α = ▼/◆

0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1 λ1 ρ(w*) L1 prior theory α=0.2 α=0.15 α=0.1 α=0.05 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1 C ρ(w*) Mixture prior theory α=0.2 α=0.15 α=0.1 α=0.05

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-44
SLIDE 44

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

▲✶ ♣r✐♦r r❡s✉❧ts✿ ♣(❉|λ✶, λ✷) ✈❡rs✉s L(✇ ∗) ❛♥❞ ρ(✇ ∗)

❈t = ✵.✷, λt = ◆/✶✵✵, α = ✵.✷

λ1 λ2/λt L(w*) 0.2 0.4 0.6 0.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 λ1 λ2/λt p(D|λ1,λ2) 0.2 0.4 0.6 0.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 ❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-45
SLIDE 45

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥ ❙t❛♥❞❛r❞ P❈❆ r❡s✉❧t ❘❡s✉❧ts ❢♦r s♣❛rs❡ P❈❆ ✭❈❁✶✮ ❘❡s✉❧ts ❢♦r ✇❡❧❧✲♠❛t❝❤❡❞ ❞❛t❛ ❘❡s✉❧ts ❢♦r ✉♥♠❛t❝❤❡❞ ❞❛t❛ ▲✶ ♣r✐♦r

▲✶ ♣r✐♦r r❡s✉❧ts✿ ♣(❉|λ✶, λ✷) ✈❡rs✉s L(✇ ∗) ❛♥❞ ρ(✇ ∗)

❈t = ✵.✷, λt = ◆/✶✵✵, α = ✵.✷

λ1 λ2/λt ρ(w*) 0.2 0.4 0.6 0.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 λ1 λ2/λt p(D|λ1,λ2) 0.2 0.4 0.6 0.8 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 ❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-46
SLIDE 46

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❉✐s❝✉ss✐♦♥

◮ ▼✐①t✉r❡ ♣r✐♦r ✇♦r❦s ❛s ❡①♣❡❝t❡❞ ✇❤❡♥ ✇❡❧❧✲♠❛t❝❤❡❞ t♦ ❞❛t❛

▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ ❢♦r ♠✐①t✉r❡ ♣r✐♦r ❝❛♥ ❜❡ ♠✐s❧❡❛❞✐♥❣ ▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ s❡❡♠s ♠♦r❡ ❡✛❡❝t✐✈❡ ❢♦r ▲✶ ♣r✐♦r ✳ ✳ ✳ ❛❧t❤♦✉❣❤ ▲✶ ❞✐❞♥✬t r❡❛❧❧② ♣❡r❢♦r♠ ✇❡❧❧ ✭♣r❡❧✐♠✐♥❛r②✮ ❋✉t✉r❡ ✇♦r❦ s❤♦✉❧❞ ❧♦♦❦ ❛t ♠✉❧t✐♣❧❡ ❢❛❝t♦rs ❆ss❡ss♠❡♥t ♦❢ ♠❡tr✐❝s ✉s✐♥❣ t❤❡ ❢✉❧❧ ♣♦st❡r✐♦r ❈♦♠♣❛r✐s♦♥ ✇✐t❤ ▼❆P ❛♥❞ ▼▲ ❛♣♣r♦❛❝❤❡s ❆♥❞ ❜❡tt❡r ♣r✐♦rs✦

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-47
SLIDE 47

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❉✐s❝✉ss✐♦♥

◮ ▼✐①t✉r❡ ♣r✐♦r ✇♦r❦s ❛s ❡①♣❡❝t❡❞ ✇❤❡♥ ✇❡❧❧✲♠❛t❝❤❡❞ t♦ ❞❛t❛ ◮ ▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ ❢♦r ♠✐①t✉r❡ ♣r✐♦r ❝❛♥ ❜❡ ♠✐s❧❡❛❞✐♥❣

▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ s❡❡♠s ♠♦r❡ ❡✛❡❝t✐✈❡ ❢♦r ▲✶ ♣r✐♦r ✳ ✳ ✳ ❛❧t❤♦✉❣❤ ▲✶ ❞✐❞♥✬t r❡❛❧❧② ♣❡r❢♦r♠ ✇❡❧❧ ✭♣r❡❧✐♠✐♥❛r②✮ ❋✉t✉r❡ ✇♦r❦ s❤♦✉❧❞ ❧♦♦❦ ❛t ♠✉❧t✐♣❧❡ ❢❛❝t♦rs ❆ss❡ss♠❡♥t ♦❢ ♠❡tr✐❝s ✉s✐♥❣ t❤❡ ❢✉❧❧ ♣♦st❡r✐♦r ❈♦♠♣❛r✐s♦♥ ✇✐t❤ ▼❆P ❛♥❞ ▼▲ ❛♣♣r♦❛❝❤❡s ❆♥❞ ❜❡tt❡r ♣r✐♦rs✦

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-48
SLIDE 48

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❉✐s❝✉ss✐♦♥

◮ ▼✐①t✉r❡ ♣r✐♦r ✇♦r❦s ❛s ❡①♣❡❝t❡❞ ✇❤❡♥ ✇❡❧❧✲♠❛t❝❤❡❞ t♦ ❞❛t❛ ◮ ▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ ❢♦r ♠✐①t✉r❡ ♣r✐♦r ❝❛♥ ❜❡ ♠✐s❧❡❛❞✐♥❣ ◮ ▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ s❡❡♠s ♠♦r❡ ❡✛❡❝t✐✈❡ ❢♦r ▲✶ ♣r✐♦r

✳ ✳ ✳ ❛❧t❤♦✉❣❤ ▲✶ ❞✐❞♥✬t r❡❛❧❧② ♣❡r❢♦r♠ ✇❡❧❧ ✭♣r❡❧✐♠✐♥❛r②✮ ❋✉t✉r❡ ✇♦r❦ s❤♦✉❧❞ ❧♦♦❦ ❛t ♠✉❧t✐♣❧❡ ❢❛❝t♦rs ❆ss❡ss♠❡♥t ♦❢ ♠❡tr✐❝s ✉s✐♥❣ t❤❡ ❢✉❧❧ ♣♦st❡r✐♦r ❈♦♠♣❛r✐s♦♥ ✇✐t❤ ▼❆P ❛♥❞ ▼▲ ❛♣♣r♦❛❝❤❡s ❆♥❞ ❜❡tt❡r ♣r✐♦rs✦

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-49
SLIDE 49

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❉✐s❝✉ss✐♦♥

◮ ▼✐①t✉r❡ ♣r✐♦r ✇♦r❦s ❛s ❡①♣❡❝t❡❞ ✇❤❡♥ ✇❡❧❧✲♠❛t❝❤❡❞ t♦ ❞❛t❛ ◮ ▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ ❢♦r ♠✐①t✉r❡ ♣r✐♦r ❝❛♥ ❜❡ ♠✐s❧❡❛❞✐♥❣ ◮ ▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ s❡❡♠s ♠♦r❡ ❡✛❡❝t✐✈❡ ❢♦r ▲✶ ♣r✐♦r ◮ ✳ ✳ ✳ ❛❧t❤♦✉❣❤ ▲✶ ❞✐❞♥✬t r❡❛❧❧② ♣❡r❢♦r♠ ✇❡❧❧ ✭♣r❡❧✐♠✐♥❛r②✮

❋✉t✉r❡ ✇♦r❦ s❤♦✉❧❞ ❧♦♦❦ ❛t ♠✉❧t✐♣❧❡ ❢❛❝t♦rs ❆ss❡ss♠❡♥t ♦❢ ♠❡tr✐❝s ✉s✐♥❣ t❤❡ ❢✉❧❧ ♣♦st❡r✐♦r ❈♦♠♣❛r✐s♦♥ ✇✐t❤ ▼❆P ❛♥❞ ▼▲ ❛♣♣r♦❛❝❤❡s ❆♥❞ ❜❡tt❡r ♣r✐♦rs✦

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-50
SLIDE 50

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❉✐s❝✉ss✐♦♥

◮ ▼✐①t✉r❡ ♣r✐♦r ✇♦r❦s ❛s ❡①♣❡❝t❡❞ ✇❤❡♥ ✇❡❧❧✲♠❛t❝❤❡❞ t♦ ❞❛t❛ ◮ ▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ ❢♦r ♠✐①t✉r❡ ♣r✐♦r ❝❛♥ ❜❡ ♠✐s❧❡❛❞✐♥❣ ◮ ▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ s❡❡♠s ♠♦r❡ ❡✛❡❝t✐✈❡ ❢♦r ▲✶ ♣r✐♦r ◮ ✳ ✳ ✳ ❛❧t❤♦✉❣❤ ▲✶ ❞✐❞♥✬t r❡❛❧❧② ♣❡r❢♦r♠ ✇❡❧❧ ✭♣r❡❧✐♠✐♥❛r②✮ ◮ ❋✉t✉r❡ ✇♦r❦ s❤♦✉❧❞ ❧♦♦❦ ❛t ♠✉❧t✐♣❧❡ ❢❛❝t♦rs

❆ss❡ss♠❡♥t ♦❢ ♠❡tr✐❝s ✉s✐♥❣ t❤❡ ❢✉❧❧ ♣♦st❡r✐♦r ❈♦♠♣❛r✐s♦♥ ✇✐t❤ ▼❆P ❛♥❞ ▼▲ ❛♣♣r♦❛❝❤❡s ❆♥❞ ❜❡tt❡r ♣r✐♦rs✦

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-51
SLIDE 51

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❉✐s❝✉ss✐♦♥

◮ ▼✐①t✉r❡ ♣r✐♦r ✇♦r❦s ❛s ❡①♣❡❝t❡❞ ✇❤❡♥ ✇❡❧❧✲♠❛t❝❤❡❞ t♦ ❞❛t❛ ◮ ▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ ❢♦r ♠✐①t✉r❡ ♣r✐♦r ❝❛♥ ❜❡ ♠✐s❧❡❛❞✐♥❣ ◮ ▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ s❡❡♠s ♠♦r❡ ❡✛❡❝t✐✈❡ ❢♦r ▲✶ ♣r✐♦r ◮ ✳ ✳ ✳ ❛❧t❤♦✉❣❤ ▲✶ ❞✐❞♥✬t r❡❛❧❧② ♣❡r❢♦r♠ ✇❡❧❧ ✭♣r❡❧✐♠✐♥❛r②✮ ◮ ❋✉t✉r❡ ✇♦r❦ s❤♦✉❧❞ ❧♦♦❦ ❛t ♠✉❧t✐♣❧❡ ❢❛❝t♦rs ◮ ❆ss❡ss♠❡♥t ♦❢ ♠❡tr✐❝s ✉s✐♥❣ t❤❡ ❢✉❧❧ ♣♦st❡r✐♦r

❈♦♠♣❛r✐s♦♥ ✇✐t❤ ▼❆P ❛♥❞ ▼▲ ❛♣♣r♦❛❝❤❡s ❆♥❞ ❜❡tt❡r ♣r✐♦rs✦

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-52
SLIDE 52

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❉✐s❝✉ss✐♦♥

◮ ▼✐①t✉r❡ ♣r✐♦r ✇♦r❦s ❛s ❡①♣❡❝t❡❞ ✇❤❡♥ ✇❡❧❧✲♠❛t❝❤❡❞ t♦ ❞❛t❛ ◮ ▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ ❢♦r ♠✐①t✉r❡ ♣r✐♦r ❝❛♥ ❜❡ ♠✐s❧❡❛❞✐♥❣ ◮ ▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ s❡❡♠s ♠♦r❡ ❡✛❡❝t✐✈❡ ❢♦r ▲✶ ♣r✐♦r ◮ ✳ ✳ ✳ ❛❧t❤♦✉❣❤ ▲✶ ❞✐❞♥✬t r❡❛❧❧② ♣❡r❢♦r♠ ✇❡❧❧ ✭♣r❡❧✐♠✐♥❛r②✮ ◮ ❋✉t✉r❡ ✇♦r❦ s❤♦✉❧❞ ❧♦♦❦ ❛t ♠✉❧t✐♣❧❡ ❢❛❝t♦rs ◮ ❆ss❡ss♠❡♥t ♦❢ ♠❡tr✐❝s ✉s✐♥❣ t❤❡ ❢✉❧❧ ♣♦st❡r✐♦r ◮ ❈♦♠♣❛r✐s♦♥ ✇✐t❤ ▼❆P ❛♥❞ ▼▲ ❛♣♣r♦❛❝❤❡s

❆♥❞ ❜❡tt❡r ♣r✐♦rs✦

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s

slide-53
SLIDE 53

P♦♣✉❧❛r s♣❛rs✐t② ♣r✐♦rs ❙♣❛rs❡ ❇❛②❡s✐❛♥ ❢❛❝t♦r ❛♥❛❧②s✐s ❆✈❡r❛❣❡ ❝❛s❡ t❤❡♦r② ❘❡s✉❧ts ❉✐s❝✉ss✐♦♥

❉✐s❝✉ss✐♦♥

◮ ▼✐①t✉r❡ ♣r✐♦r ✇♦r❦s ❛s ❡①♣❡❝t❡❞ ✇❤❡♥ ✇❡❧❧✲♠❛t❝❤❡❞ t♦ ❞❛t❛ ◮ ▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ ❢♦r ♠✐①t✉r❡ ♣r✐♦r ❝❛♥ ❜❡ ♠✐s❧❡❛❞✐♥❣ ◮ ▼❛r❣✐♥❛❧ ❧✐❦❡❧✐❤♦♦❞ s❡❡♠s ♠♦r❡ ❡✛❡❝t✐✈❡ ❢♦r ▲✶ ♣r✐♦r ◮ ✳ ✳ ✳ ❛❧t❤♦✉❣❤ ▲✶ ❞✐❞♥✬t r❡❛❧❧② ♣❡r❢♦r♠ ✇❡❧❧ ✭♣r❡❧✐♠✐♥❛r②✮ ◮ ❋✉t✉r❡ ✇♦r❦ s❤♦✉❧❞ ❧♦♦❦ ❛t ♠✉❧t✐♣❧❡ ❢❛❝t♦rs ◮ ❆ss❡ss♠❡♥t ♦❢ ♠❡tr✐❝s ✉s✐♥❣ t❤❡ ❢✉❧❧ ♣♦st❡r✐♦r ◮ ❈♦♠♣❛r✐s♦♥ ✇✐t❤ ▼❆P ❛♥❞ ▼▲ ❛♣♣r♦❛❝❤❡s ◮ ❆♥❞ ❜❡tt❡r ♣r✐♦rs✦

❇❛②❡s✐❛♥ ❧❡❛r♥✐♥❣ ♦❢ s♣❛rs❡ ❢❛❝t♦r ❧♦❛❞✐♥❣s