Finding the Principal Points of a Random Variable

Emilio Carrizosa, E Conde, A Castaño, Dolores Romero Morales

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Resumé

The p-principal points of a random variable X with finite second moment are those p points in ${\mathbb R}$ minimizing the expected squared distance from X to the closest point. Although the determination of principal points involves in general the resolution of a multiextremal optimization problem, existing procedures in the literature provide just a local optimum. In this paper we show that standard Global Optimization techniques can be applied.
OriginalsprogEngelsk
TidsskriftR A I R O - Operations Research
Vol/bind35
Udgave nummer3
Sider (fra-til)315-328
ISSN0399-0559
DOI
StatusUdgivet - 2001
Udgivet eksterntJa

Emneord

  • Principal points
  • D.C. functions
  • Branch and bound

Citer dette

Carrizosa, Emilio ; Conde, E ; Castaño, A ; Romero Morales, Dolores . / Finding the Principal Points of a Random Variable. I: R A I R O - Operations Research. 2001 ; Bind 35, Nr. 3. s. 315-328.
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Finding the Principal Points of a Random Variable. / Carrizosa, Emilio; Conde, E; Castaño, A; Romero Morales, Dolores .

I: R A I R O - Operations Research, Bind 35, Nr. 3, 2001, s. 315-328.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - Finding the Principal Points of a Random Variable

AU - Carrizosa, Emilio

AU - Conde, E

AU - Castaño, A

AU - Romero Morales, Dolores

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N2 - The p-principal points of a random variable X with finite second moment are those p points in ${\mathbb R}$ minimizing the expected squared distance from X to the closest point. Although the determination of principal points involves in general the resolution of a multiextremal optimization problem, existing procedures in the literature provide just a local optimum. In this paper we show that standard Global Optimization techniques can be applied.

AB - The p-principal points of a random variable X with finite second moment are those p points in ${\mathbb R}$ minimizing the expected squared distance from X to the closest point. Although the determination of principal points involves in general the resolution of a multiextremal optimization problem, existing procedures in the literature provide just a local optimum. In this paper we show that standard Global Optimization techniques can be applied.

KW - Principal points

KW - D.C. functions

KW - Branch and bound

U2 - 10.1051/ro:2001117

DO - 10.1051/ro:2001117

M3 - Journal article

VL - 35

SP - 315

EP - 328

JO - R A I R O - Operations Research

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SN - 0399-0559

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