Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
第4回 確率・統計の基礎勉強会
Search
setten-QB
March 25, 2017
Education
210
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
第4回 確率・統計の基礎勉強会
研究室のM1向け勉強会のスライド
setten-QB
March 25, 2017
More Decks by setten-QB
See All by setten-QB
機械学習とセキュリティ
settenqb
8
2k
確率・統計の基礎勉強会3
settenqb
0
280
確率・統計勉強会2
settenqb
0
180
確率・統計の基礎勉強会1
settenqb
1
300
Other Decks in Education
See All in Education
[2026前期火5] 論理学(京都大学文学部 前期 第14回)「計算は、証明ではない——ハルシネーションを三層ハーモニーで診る」
yatabe
0
220
Lectura 2 (PIT : Python Basico)
robintux
0
430
Adobe Express
matleenalaakso
2
8.3k
輻射安全管理系統2.0暨輻防e++學園平台說明會
aecrp
0
1.9k
エビデンスベースト英語教育入門:エビデンスは科学的知見(だけ)ではない,制度だ!
terasawat
0
180
Del ojo entrenado a la visión computacional: evaluación de la severidad de enfermedades
emdelponte
0
120
1人 × AI、1か月でここまで作れる ー 数年前の外注換算3.8〜7.4億円・241〜379人月分の作業を、AI費用 約10万円・31日で
frievea
0
430
人間のために、人間と共に働く時代の終わりの始まり
frievea
0
150
Case Studies and Future Research - Lecture 12 - Next Generation User Interfaces (4018166FNR)
signer
PRO
0
250
2026年度春学期 統計学 第8回(オンデマンド配信回) 演習(1)・問題に対する答案の書き方 (2026. 5. 21)
akiraasano
PRO
0
190
2026年度春学期 統計学 第10回 分布の推測とは - 標本調査,度数分布と確率分布 (2026. 6. 4)
akiraasano
PRO
0
190
Antigravityを使ってGeminiAPI(NanobananaPro)と連携して挿絵メーカーを作った
yoshimura_datam
0
180
Featured
See All Featured
16th Malabo Montpellier Forum Presentation
akademiya2063
PRO
0
360
HDC tutorial
michielstock
2
820
Accessibility Awareness
sabderemane
1
180
The Pragmatic Product Professional
lauravandoore
37
7.4k
Claude Code どこまでも/ Claude Code Everywhere
nwiizo
67
57k
Art, The Web, and Tiny UX
lynnandtonic
304
22k
The Organizational Zoo: Understanding Human Behavior Agility Through Metaphoric Constructive Conversations (based on the works of Arthur Shelley, Ph.D)
kimpetersen
PRO
0
430
RailsConf 2023
tenderlove
30
1.5k
Helping Users Find Their Own Way: Creating Modern Search Experiences
danielanewman
31
3.3k
Building Adaptive Systems
keathley
44
3.2k
Keith and Marios Guide to Fast Websites
keithpitt
413
23k
How to train your dragon (web standard)
notwaldorf
97
6.8k
Transcript
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ
ాத ণ (@setten QB) ಸྑઌՊֶٕज़େֶӃେֶ ใՊֶݚڀՊɹɹೳίϛϡχέʔγϣϯݚڀࣨ Ϗοάσʔλάϧʔϓ March 25, 2017 ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 1 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ 1 Introduction 2 Ծઆݕఆ 3
2 छྨͷաޡͱݕग़ྗؔ 4 ࠷ڧྗݕఆͷߏ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 2 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ౷ܭతݕఆ • ౷ܭతਪఆཧͱڞʹ౷ܭతਪଌཧͷ 2 େபΛ͢
• “ͳΜͪΌͬͯ౷ܭֶ”ͷߨٛͰݕఆͷΓํ͚ͩڭ͑Δॴ͋Δ Β͍͠ • ඪຊ͕ै͏֬ʹؔ͢Δ໋ (͜ΕΛԾઆͱݺͿ) ͕ਖ਼͍͠ͷ͔Λ σʔλʹج͍ͮͯஅ͢Δํ๏ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 3 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ 1 Introduction 2 Ծઆݕఆ 3
2 छྨͷաޡͱݕग़ྗؔ 4 ࠷ڧྗݕఆͷߏ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 4 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ Ծઆݕఆ • લճͷ౷ܭతਪఆཧͱಉ༷ͷԾఆΛ͓͘ ౷ܭతਪଌͷجຊతઃఆ ඪຊ
X1, . . . , Xn iid ∼ f(x; θ) ʹج͖ͮɼਪఆྔ θ = θ(X1, . . . , Xn) Ͱ θ Λਪఆ͢Δɽ • f(x, θ) ͷະύϥϝʔλ θ ʹؔ͢ΔԾઆΛɼσʔλʹج͍ͮͯغ٫͢ Δ͔൱͔Λܾఆ͢Δ͜ͱΛ౷ܭతݕఆͱ͍͏ • ύϥϝʔλ θ ؚ͕·ΕΔۭؒΛ Θ Ͱද͢ • Θ0, Θ1 ⊂ Θ ͕ Θ0, Θ1 ̸= ∅, Θ1 ∩ Θ1 = ∅, Θ0 ∪ Θ1 = Θ ͱ͢Δ • ҰൠతʹԾઆ • ؼແԾઆ (null hypothesis) H0 : θ ∈ Θ0 • ରཱԾઆ (alternative hypothesis) H1 : θ1 ∈ Θ1 Ͱߏ͞ΕΔ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 5 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ Ծઆݕఆ • null hypothesis ʹغ٫͍ͨ͠ԾઆΛ͓͘ͷ͕ී௨
• null hypothesis ͷඪຊͷΑ͏ͳσʔλ͕ಘΒΕΔ֬Λߟ͑ɼͦͷΑ ͏ͳ͜ͱ͕ “ى͜Γʹ͍͘”ͱߟ͑ͨ࣌ɼnull hypothesis Λ reject ͢Δ • null hypothesis Λ reject ग़དྷͨͱ͖ɼͦΕͱରཱ͢Δ alternative hypothesis Λ accept ͢Δ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 6 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ౷ܭతԾઆݕఆͷྫ ⃝ ൪͘͡ ςϥγϚ܅ɼίϯϏχͰߦΘΕ͍ͯΔ͘͡Ҿ͖ʹߦͬͨɽ൴ͷૂ ͍
A ͷσϏϧʔΫͷԦঁͷϑΟΪϡΞͰɼͦΕҎ֎ʹڵຯ ͳ͍ɽެࣜʹΑΔͱ 60 ຕͷΫδͷதʹ 2 ຕͷׂ߹Ͱ A ͕ೖͬ ͍ͯΔͱ͍͏ɽͨͩ͠ɼ͜ͷίϯϏχಛघͰɼͨΓͱϋζϨͷׂ ߹͕ৗʹҰఆʹͳΔΑ͏ʹ٬͕͘͡ΛҾͨ͘ͼʹ৽͍͠ΫδΛՃ ͢ΔɽςϥγϚ͘Μ 1 ϲ݄ͷֶۚΛͭ͗ࠐΜͰ 200 ຕͷΫδ ΛҾ͍ͨɽ͔͠͠ɼA 1 ຕ͔͠Ҿ͚ͳ͔ͬͨɽ͜ͷίϯϏχ ΠϯνΩΛ͍ͯ͠Δͱݴ͑Δ͔ʁ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 7 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ౷ܭతԾઆݕఆͷྫ • A ΛҾ֬͘Λ p
ͱ͢Δ • ΠϯνΩΛ͍ͯ͠Δͱओு͍ͨ͠ςϥγϚ܅ཱ͕ͯΔԾઆ H0 : p = 1/30 vs H1 : p ̸= 1/30 • θ = p, Θ = (0, 1), Θ0 = { 1/30 } , Θ1 = (0, 1) − { 1/30 } • ςϥγϚ܅͕Ҿ͍ͨ͘͡ X1, . . . , X200 iid ∼ B(1, p) ͷ࣮ݱͱߟ͑Β ΕΔ • ͨͩ͠ɼA Λ 1ɼͦΕҎ֎Λ 0 ͱ͢Δ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 8 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ౷ܭతԾઆݕఆͷྫ • A ΛҾ͘ຕΛ Y
ͱ͢Δͱɼ Y = 200 ∑ i=1 ∼ B(200, p) Ͱ͋Δ • Αͬͯɼ1 ճ͔͠ A ΛҾ͔ͳ͍֬ P(Y = 1) = ( 200 1 ) p1(1 − p)199 ͱॻ͚Δ • H0 ͕ਖ਼͍͠ͱ͍͏ԾఆͷͱͰɼP(Y = 1) = 0.00783 ͱͳΔ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 9 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ౷ܭతԾઆݕఆͷྫ • ͜͜·ͰͷٞͰɼH0 ͕ਅͰ͋ΔͱԾఆ͢Δͱʮ200 ຕҾ͍ͯ
A ͕ 1 ճ͔ͨ͠Βͳ͍ʯͱ͍͏ঢ়گ͕ى͜Δ֬ 1% ʹຬͨͳ͍͜ͱ ʹͳΔ • ͜ͷΑ͏ͳح͕ى͜ΔΑΓɼH0 ͕͓͔͍͠ͱ͢Δ΄͏͕ࣗવͰ ͋Δ • ͕ͨͬͯ͠ɼH0 Λ reject ͠ H1 Λ accept ͢Δ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 10 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ౷ܭతԾઆݕఆͷྫ • ͜͜·ͰͷٞͰɼH0 ͕ਅͰ͋ΔͱԾఆ͢Δͱʮ200 ຕҾ͍ͯ
A ͕ 1 ճ͔ͨ͠Βͳ͍ʯͱ͍͏ঢ়گ͕ى͜Δ֬ 1% ʹຬͨͳ͍͜ͱ ʹͳΔ • ͜ͷΑ͏ͳح͕ى͜ΔΑΓɼH0 ͕͓͔͍͠ͱ͢Δ΄͏͕ࣗવͰ ͋Δ • ͕ͨͬͯ͠ɼH0 Λ reject ͠ H1 Λ accept ͢Δ ͭ·Γ౷ܭֶతʹߟ͑ͯɼ͜ͷίϯϏχΠϯνΩΛ͍ͯ͠Δ! ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 10 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ غ٫Ҭ • Ծઆݕఆ · ·
· • ूஂ͔Βͷແ࡞ҝඪຊ X = [X1 , . . . , Xn ] ͷऔΓ͏Δͷू߹ͷ ෦ू߹ C ΛఆΊΔ • X ͷ࣮ݱ͕ C ʹଐ͢Δ࣌ʹ H0 Λغ٫͢Δ ͱ͍͏ϧʔϧͰߏ͞Ε͍ͯΔ • ʮX ͕ͲͷΑ͏ͳΛऔΕ H0 Λغ٫͢Δ͔ʁʯͱ͍͏ϧʔϧΛܾ ΊΔ͜ͱ͕ݕఆΛߏ͢Δͱ͍͏͜ͱ • ্هͷ C Λݕఆͷغ٫ҬͱݺͿ • ʮ“ྑ͍” غ٫ҬΛͲͷΑ͏ʹܾΊΔͷ͔ʁ͕ʯͱͳΔ • ͳ͓ɼH0 Λغ٫ग़དྷͳ͔͔ͬͨΒͱݴͬͯɼH0 Λੵۃతʹࢧ࣋͢Δ Θ͚Ͱͳ͍͜ͱʹҙ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 11 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ 1 Introduction 2 Ծઆݕఆ 3
2 छྨͷաޡͱݕग़ྗؔ 4 ࠷ڧྗݕఆͷߏ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 12 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ 2 छྨͷաޡ • ʮओு A
͕ਖ਼͍͠ͷ͔ʁʯͱ͍͏ࣄΛஅ͢Δঢ়گΛߟ͑Δ • ͜ͷΑ͏ͳঢ়گʹ͓͍ͯɼඞͣද 1 ʹࣔ͢Α͏ͳޡΓ͕ى͜ΓಘΔ Table: 2 छྨͷաޡ ਅ࣮ H0 H1 H0 ⃝ Type II Error ஈ H1 Type I Error ⃝ • θ ∈ Θ0 ͭ·Γ H0 ཱ͕͍ͯ͠ΔԼͰͷࣄ A ͷ֬Λ Pθ(A), Pθ(A|θ ∈ Θ0), Pθ(A|H0) ͳͲͰද͢ 1 • Type I Error, Type II Error ͷ֬ͦΕͧΕ Pθ(X / ∈ C|H0), Pθ(X ∈ C|H1) ͱॻ͚Δ 1͖݅֬Ͱͳ͍͜ͱʹҙ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 13 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ݕग़ྗ ݕग़ྗؔ ؔ β :
θ → [0, 1] Λ β(θ) = Pθ (X ∈ C) (1) ͰఆΊɼݕఆͷݕग़ྗؔͱ͍͏ɽಛʹɼθ1 ∈ Θ1 ͷͱ͖ β(θ1) Λ θ1 ʹର͢Δݕఆͷݕग़ྗ (Power) ͱ͍͏ɽ • ݕग़ྗ H1 ͕ਅͷ࣌ʹɼH0 Λਖ਼͘͠غ٫Ͱ͖Δ֬Λද͍ͯ͠Δ • Type I Error ͷ֬ β(θ), θ ∈ Θ0 • Type II Error ͷ֬ 1 − β(θ), θ ∈ Θ1 ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 14 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ݕఆؔ ݕఆؔ X = [X1,
. . . , Xn] ͷ࣮ݱ x = [x1, . . . , xn] ͷؔ φ (x) = 1{ X∈C } = { 1 (x ∈ C) 0 (x / ∈ C) Λݕఆؔͱ͍͏ɽ • ݕఆؔͷ͜ͱΛݕఆͱ͍͏͜ͱ͋Δ • ݕఆؔΛ໌ࣔ͢Δ͜ͱΛݕఆΛߏ͢Δͱ͍͏ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 15 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ݕఆͷߏྫ ݕఆͷߏͱաޡͷ֬ ֬ม X ͷ͕ؔ
Fθ(x) = 1 − exp(−θx) Ͱ͋Δͱ͖ɼ H0 : θ = 1 vs H1 : θ > 1 ͷݕఆΛߟ͑ΔɽݕఆؔΛ φ(x) = { 1 (x > 2) 0 (x ≤ 2) ͱ͢ΔɽҎԼͷʹ͑Αɽ (1) Tyepe II Error ͷ֬ΛٻΊɼθ ʹ͍ͭͯͷάϥϑΛඳ͚ɽ (2) Type I Error ͷ֬ΛٻΊΑɽ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 16 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ݕఆͷߏྫ (1). ·ͣɼغ٫Ҭ C =
{ x | x > 2 }ɽΑͬͯɼType II Error ͷ֬ P(X / ∈ C|H1) =P(X ≤ 2|θ > 1) =Fθ(2) =1 − exp(−2θ) (θ > 1). (2). Type I Error ͷ֬ P(X ∈ C|H0) =P(X > 2|θ = 1) =1 − F1(2) = exp(2). ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 17 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ 1 Introduction 2 Ծઆݕఆ 3
2 छྨͷաޡͱݕग़ྗؔ 4 ࠷ڧྗݕఆͷߏ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 18 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ 2 छྨͷ Error ֬ •
Type I Error ͷ֬ͱ Type II Error ͷ֬Λখ͍ͨ͘͞͠ • ͔͠͠ɼ2 ͭͷ֬Λಉ࣌ʹ࠷খԽग़དྷͳ͍ • ͰͲ͏͢Δͷ͔ʁ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 19 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ 2 छྨͷ Error ֬ •
Type I Error ͷ֬ͱ Type II Error ͷ֬Λখ͍ͨ͘͞͠ • ͔͠͠ɼ2 ͭͷ֬Λಉ࣌ʹ࠷খԽग़དྷͳ͍ • ͰͲ͏͢Δͷ͔ʁ P (X ∈ C|θ ∈ Θ1) ≤ α ͷԼͰ Pθ (X ∈ C|θ ∈ Θ1) Λ࠷େԽ͢ΔΑ͏ͳݕ ఆΛߏ͢Δ! • ఆ α લܾͬͯΊ͓ͯ͘ఆͰɼ“༗ҙਫ४” ͱ͍͏ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 19 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ࠷ڧྗݕఆ ࠷ڧྗݕఆ • Φα =
{ φ | Eθ [φ (X)] , θ ∈ Θ0 } • θ1 ∈ Θ1 β(θ) Λ࠷େʹ͢Δ φ ∈ Φα Λɼ༗ҙਫ४ α ͷ θ = θ1 ʹର͢Δ࠷ڧ ྗݕఆ (Most Powerful Test; MP ݕఆ) ͱ͍͏ɽ∀θ ∈ Θ1 Ͱ β(θ) Λ ࠷େʹ͢Δ φ ∈ Φα ΛҰ༷࠷ڧྗݕఆ (Uniformly MP ݕఆ) ͱ͍͏ɽ • Ұ༷࠷ڧྗݕఆ͕ଘࡏ͢ΕɼଞͷݕఆΛߏ͢Δඞཁͳ͍ • ͰɼҰ༷࠷ڧྗݕఆͲͷΑ͏ʹߏ͞ΕΔͷ͔? ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 20 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ Neyman-Pearson ͷجຊఆཧ ωΠϚϯɾϐΞιϯͷجຊఆཧ X1, .
. . Xn iid ∼ f(x; θ) ͱ͢Δɽݕఆ H0 : θ = θ0 vs H1 : θ = θ1 Λߟ͑Δɽf0(x) = ∏ n i=1 f(x; θ0), f1(x) = ∏ n i=1 f(x; θ1), ͱ͢Δ ͱɼ༗ҙਫ४ α (0 < α < 1) ͷ MP ݕఆ ϕ (x) = 1 (f1(x) > kf0(x)) γ (f1(x) = kf0(x)) 0 (f1(x) ≤ kf0(x)) Ͱ༩͑ΒΕΔɽ͜͜Ͱ k, γ Eθ0 [φ (X)] = α Λຬͨ͢ఆ (k ≥ 0, 0 ≤ γ ≤ 1) Ͱ͋Δɽ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 21 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ൺ ൺ H0, H1 ͷԼͰͷ
p.d.f. (p.m.f.) ͷൺ Λ (x) = f1 (x) f0 (x) Λൺͱ͍͏ɽ • Neyman-Peason ͷجຊఆཧɼൺʹج͍ͮͯ MP ݕఆ͕ߏ͞Ε Δ͜ͱΛ͍ࣔͯ͠Δ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 22 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ MP ݕఆͷߏྫ MP ݕఆͷߏྫ –ਖ਼نΛྫʹ–
X1, . . . , Xn iid ∼ N ( µ, σ2 ) ɼσ2ɿطɼµɿະͱ͍͏ঢ়گͰɼݕఆ H0 : µ = µ0 vs H1 : µ = µ1 > µ0 Λߟ͑Δɽ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 23 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ MP ݕఆͷߏྫ H0 ͷԼͰͷ j.p.d.f.
f0 (x) = ( 1 √ 2πσ2 )n exp [ − 1 2σ2 n ∑ i=1 (xi − µ0 )2 ] H1 ͷԼͰͷ j.p.d.f. f1 (x) = ( 1 √ 2πσ2 )n exp [ − 1 2σ2 n ∑ i=1 (xi − µ1 )2 ] Ͱ͋Δ͔Βɼൺ Λ (x) = exp [ − 1 2σ2 n ∑ i=1 (xi − µ1 )2 + 1 2σ2 n ∑ i=1 (xi − µ1 )2 ] = exp [ n (µ1 − µ0 ) σ2 x − n ( µ2 1 − µ2 0 )] ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 24 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ MP ݕఆͷߏྫ X1, . .
. , Xn C-type ͳͷͰ φ (x) = { 1 Λ (x) > k 0 Λ (x) < k ͕࠷ڧྗݕఆͰ͋ΔɽΛ (x) ͕୯ௐ૿ՃؔͰ͋Δ͜ͱ͔Β ∃k′ ∈ R s.t. Λ (x) > k ⇐⇒ x > k′. ༗ҙਫ४Λ α > 0 ͱ͢Δͱ α = Eµ0 [φ (X)] = ∫ Λ(x)>0 dFµ0 (x) =Pµ0 (Λ(X) > k|H0) =Pµ0 ( X > k′|H0 ) ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 25 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ MP ݕఆͷߏྫ √ n (
X − µ0 ) /σ ∼ N (0, 1) Ͱ͋Δ͜ͱΛ༻͍Δͱɼ α = P ( √ n ( X − µ0 ) σ > √ n (k′ − µ0 ) σ µ0 ) = 1 − Φ (√ n (k′ − µ0 ) σ ) ͱͳΔɽzα Λ N (0, 1) ͷ্ଆ 100α% ͱ͢Δͱɼ zα = √ n (k′ − µ0) σ =⇒ k′ = µ0 + σ √ n zα Ͱ͋Δ͔Βɼ࠷ڧྗݕఆͷغ٫Ҭͱͯ͠ C = { (x1, . . . , xn) x > µ0 + σ √ n zα } ͕ٻ·Δɽ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 26 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ MP ݕఆͷߏྫ • ͜ͷغ٫Ҭ C
ɼµ1 ͷʹґଘ͍ͯ͠ͳ͍ͷͰɼµ1 > µ0 Λຬͨ͢ ҙͷ µ1 ʹରͯ͠ಉ༷ͷغ٫Ҭ͕ಋ͔ΕΔ • ͕ͨͬͯ͠ɼ͜ͷݕఆ UMP ݕఆͰ͋Δ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 27 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ MP ݕఆͷߏྫ –Type II Error
ͷ֬– ࣍ʹɼType II Error ͷ֬ΛٻΊΔɽµ = µ1 ͷͱ͖ʹ X / ∈ C ͱͳΔ֬ ͳͷͰɼ P ( X / ∈ C µ1 ) =P ( X < µ0 + σ √ n zα ) =P (√ n ( X − µ1 ) σ < zα − √ n (µ0 − µ1) σ ) =Φ ( zα − √ n (µ0 − µ1) σ ) . α Λখ͘͢͞ΔͱɼఆٛΑΓ zα େ͖͘ͳΔͷͰɼType II Error ͷ֬ େ͖͘ͳΔɽ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 28 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ MP ݕఆͷߏྫ – ݕग़ྗ –
ݕग़ྗ β(µ1) =P ( X ∈ C µ1 ) =1 − P ( X / ∈ C µ1 ) =1 − Φ ( zα − √ n (µ0 − µ1) σ ) ͱٻ·Δɽ • ݕग़ྗ β(µ1) ɼµ0 − µ1 ͕େ͖͍΄Ͳେ͖͘ͳΔ • 2 ܈ͷฏۉ͕େ͖͘Ε͍ͯΔ΄Ͳ H0 ཱ͕͍ͯ͠Δ͔ H1 ཱ͕ ͍ͯ͠Δͷ͔Λݟ͚Δͷ؆୯ͱ͍͏ײʹ߹க͍ͯ͠Δ • n ͕େ͖͍΄Ͳݕग़ྗ͕େ͖͘ͳΔ • ͜Εײʹ߹க͍ͯ͠Δ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 29 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ MP ݕఆͷߏྫ • ઌఔߟ͑ͨྫ H1
: µ = µ1 > µ0 Ͱ͕͋ͬͨɼରཱԾઆͱͯ͠ H1 : µ = µ1 < µ0 ߟ͑Δ͜ͱ͕ग़དྷΔ • ͜ͷ߹ɼಉ༷ʹͯ͠࠷ڧྗݕఆͷغ٫Ҭ C = { (x1, . . . , xn) x < µ0 + σ √ n zα } ΛߏͰ͖Δ • ͜ͷΑ͏ʹɼରཱԾઆ H1 ͷؼແԾઆ H0 ͔ΒͷζϨͷํʹରԠ͠ ͯغ٫Ҭ͕ H0 ͷ (ࠓճ µ0) ยଆʹ࡞ΒΕΔݕఆΛยଆݕఆͱ͍͏ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 30 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ MP ݕఆͷߏྫ –྆ଆݕఆͷ֦ு– • ରཱԾઆ͕
H1 : µ ̸= µ0 ͷ߹ʹ༗ҙਫ४ α ͷ UMP ݕఆଘࡏ͠ ͳ͍ • ͔͠͠ɼ͜Ε·Ͱͷ͔ٞΒغ٫Ҭ C = { (x1, . . . , xn) |x − µ0| > σ √ n zα } ΛߏͰ͖Δ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 31 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ৴པ۠ؒͱݕఆ • ਖ਼نूஂʹ͓͚ΔࢄطͰͷฏۉͷ۠ؒਪఆʹ͓͍ͯɼ৴པ 100(1
− α)% ͷ µ ͷ৴པ۠ؒ Iµ = [ X − zα/2 σ0 √ n , X + zα/2 σ0 √ n ] • Iµ ͕ µ0 ΛؚΉͱ͢ΔͱɼؼແԾઆ H0 ઌఔͷ྆ଆݕఆʹ͓͍ͯ༗ ҙਫ४ α Ͱغ٫͞Εͳ͍ • ͢ͳΘͪɼx / ∈ C =⇒ µ0 ∈ Iµ • ͭ·ΓɼؼແԾઆ͕غ٫͞Εͳ͍͜ͱͱɼ৴པ͕۠ؒؼແԾઆͷΛ ؚΉ͜ͱಉɿ ؼແԾઆ͕غ٫͞ΕΔ ⇐⇒ ৴པ͕۠ؒؼແԾઆͷΛؚ·ͳ͍ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 32 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ ͦͷଞͷݕఆߏํ๏ • ࠶ڠྗݕఆωΠϚϯɾϐΞιϯͷجຊఆཧʹΑͬͯߏ͞ΕΔ͕ɼ ͕ෳࡶʹͳͬͯਖ਼֬ͳغ٫ҬΛ࡞Εͳ͍͜ͱ͋Δ •
ͦΜͳͱ͖ɼ࠷ਪఆྔʹج͍ͯݕఆΛߏ͢Δ͜ͱ͕͋Δ • ଞʹɼefficient score Λ༻͍ͨݕఆͷߏํ๏͋Δ ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 33 / 33
Introduction Ծઆݕఆ 2 छྨͷաޡͱݕग़ྗؔ ࠷ڧྗݕఆͷߏ Reference • ฏণจ, ౷ܭղੳೖ, ग़൛גࣜձࣾ,
2007 • ౻؏ଠ, ཧ౷ܭֶ II ߨٛϊʔτ, 2014 • ౦ژେֶڭཆֶ෦౷ܭֶڭࣨɼجૅ౷ܭֶ III ࣗવՊֶͷ౷ܭֶɼ2013 ాத ণ (@setten QB) (AHC-Lab) ୈ 4 ճ ֬ɾ౷ܭͷجૅษڧձ ౷ܭతݕఆ March 25, 2017 34 / 33