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Estimation of failure probability in higher-dimensional spaces
Ana Ferreira, UTL, Lisbon, PortugalLaurens de Haan, UL, Lisbon Portugal
and EUR, Rotterdam, NLTao Lin, Xiamen University, China
Research partially supported by
Fundação Calouste Gulbenkian
FCT/POCTI/FEDER – ERAS project
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A simple exampleA simple example• Take r.v.’s (R, Ф), independent,
and (X,Y) : = (R cos Ф, R sin Ф) .
• Take a Borel set A with positive distance to the origin.
• Write a A : = {a x : x A}.
• Clearly
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• Suppose: probability distribution of Ф unknown.
• We have i.i.d. observations (X1,Y1), ... (Xn,Yn), and a failure set A away from the observations in the NE corner.
• To estimate P{A} we may use a {a A} where is the empirical measure.
This is the main idea of estimation of failure set probability.
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• Some device can fail under the combined influence of extreme behaviour of two random forces X and Y. For example: rain and wind.
• “Failure set” C: if (X, Y) falls into C, then failure takes place.
• “Extreme failure set”: none of the observations we have from the past falls into C. There has never been a failure.
• Estimate the probability of “extreme failure”
The problem:The problem:
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A bit more formalA bit more formal• Suppose we have n i.i.d. observations (X1,Y1),
(X2,Y2), ... (Xn,Yn), with distribution function F and a failure set C.
• The fact “none of the n observations is in C” can be reflected in the theoretical assumption
P(C) < 1 / n .Hence C can not be fixed, we have
C = Cn
and P(Cn) = O (1/n) as n → ∞ .i.e. when n increases the set C moves, say, to the
NE corner.
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Domain of attraction condition EVTDomain of attraction condition EVTThere exist• Functions a1, a2 >0, b1, b2 real• Parameters 1 and 2
• A measure on the positive quadrant [0, ∞ ]2 \ {(0,0)} with
(a A) = a-1 (A) ⑴ for each Borel set A, such that
for each Borel set A⊂ with positive distance to the origin.
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RemarkRemark
Relation is as in the example⑴ .But here we have the marginal transformations
on top of that.
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Hence two steps:Hence two steps:
1) Transformation of marginal distributions
2) Use of homogeneity property of υ
when pulling back the failure set.
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ConditionsConditions1) Domain of attraction:
2) We need estimators
with
for i = 1,2 with k k(n)→∞ , k/n → 0, n→∞ .
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3) Cn is open and there exists (vn , wn) ∈ Cn such that (x , y) ∈ Cn ⇒ x > vn or y > wn .
4) (stability condition on Cn ) The set
in does not depend on n where
⑵
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Further : S has positive distance from the origin.
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Before we go on, we simplify notation:
NotationNotation
• Note that
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With this notation we can write
Cond. 1' :
Cond. 4' :
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Then:
Condition 5 Sharpening of cond.1:
Condition 6 1 , 2 > 1 / 2 and
for i = 1,2 where
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The EstimatorThe Estimator Note that
Hence we propose the estimator
and we shall prove
Then
•
•
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More formally:More formally:• Write: pn: P {Cn}. Our estimator is
• Where
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TheoremTheorem
Under our conditions
as n→∞ provided (S) > 0.
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For the proof note that by Cond. 5
and
Hence it is sufficient to prove
and
For both we need the following fundamental Lemma.
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LemmaLemma
For all real γ and x > 0 , if γn → γ (n→∞ ) and cn ≥ c>0,
provided
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PropositionProposition
ProofProof RecallRecall
and
Combining the two we get
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The Lemma gives
Similarly
Hence
Ɯ
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Finally we need to prove
We do this in 3 steps.
Proposition 1Proposition 1 Define
We have
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ProofProofJust calculate the characteristic function and
apply Condition 1.
Proposition 2Proposition 2 Define
we have
Next apply Lebesgue’s dominated convergence Theorem.
ProofProof
By the Lemma → identity.
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Proposition 3Proposition 3
The result follows by using statement and proof of Proposition 2
ProofProof The left hand side is
By the Lemma → identity.
end of finite-dimensional case
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Similar result in function spaceSimilar result in function space
Example:Example: During surgery the blood pressure of the patient is monitored continuously. It should not go below a certain level and it has never been in previous similar operations in the past. What is the probability that it happens during surgery of this kind?
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EVT in EVT in C [0,1]C [0,1]
1. Definition of maximum: Let X1, X2, ... be i.i.d. in C [0,1]. We consider
as an element of C [0,1].
2. Domain of attraction. For each Borel set
A ∈ C+ [0,1] with
we have
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where for 0 ≤ s ≤ 1 we define
and is a homogeneous measure of degree –1.
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ConditionsConditionsCond. 1. Domain of attraction.
Cond. 2. Need estimators
such that
Cond. 3. Failure set Cn is open in C[0,1] and there exists hn ∈ ∂Cn such that
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Cond. 4
with
a fixed set (does not depend on n) and
Further:
•
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and
•
•
Cond. 5
Cond. 6
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Now the estimator for pn: P{Cn} :
where
and
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TheoremTheoremUnder our conditions
as n→∞ provided (S) > 0.