Loading [MathJax]/extensions/tex2jax.js

Monte Carlo Algorithms for Finding the Maximum of a Random Walk with Negative Drift

Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review

Autorschaft

  • Ludwig Baringhaus
  • Rudolf Grübel

Organisationseinheiten

Plum Print visual indicator of research metrics
  • Citations
    • Citation Indexes: 1
  • Captures
    • Readers: 1
see details

Details

OriginalspracheEnglisch
Seiten (von - bis)74-86
Seitenumfang13
FachzeitschriftJournal of Applied Probability
Jahrgang43
Ausgabenummer1
PublikationsstatusVeröffentlicht - 2006

Abstract

We discuss two Monte Carlo algorithms for finding the global maximum of a simple random walk with negative drift. This problem can be used to connect the analysis of random input Monte Carlo algorithms with ideas and principles from mathematical statistics.

ASJC Scopus Sachgebiete

Zitieren

Monte Carlo Algorithms for Finding the Maximum of a Random Walk with Negative Drift. / Baringhaus, Ludwig; Grübel, Rudolf.
in: Journal of Applied Probability, Jahrgang 43, Nr. 1, 2006, S. 74-86.

Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review

Baringhaus L, Grübel R. Monte Carlo Algorithms for Finding the Maximum of a Random Walk with Negative Drift. Journal of Applied Probability. 2006;43(1):74-86. doi: 10.1239/jap/1143936244
Baringhaus, Ludwig ; Grübel, Rudolf. / Monte Carlo Algorithms for Finding the Maximum of a Random Walk with Negative Drift. in: Journal of Applied Probability. 2006 ; Jahrgang 43, Nr. 1. S. 74-86.
Download
@article{492f9e36520f402e826f479a43242a05,
title = "Monte Carlo Algorithms for Finding the Maximum of a Random Walk with Negative Drift",
abstract = "We discuss two Monte Carlo algorithms for finding the global maximum of a simple random walk with negative drift. This problem can be used to connect the analysis of random input Monte Carlo algorithms with ideas and principles from mathematical statistics.",
keywords = "Brownian motion with drift, Conditioning, Efficiency, Fast Fourier transform, Ladder variable, Markov chain, Randomization",
author = "Ludwig Baringhaus and Rudolf Gr{\"u}bel",
year = "2006",
doi = "10.1239/jap/1143936244",
language = "English",
volume = "43",
pages = "74--86",
journal = "Journal of Applied Probability",
issn = "0021-9002",
publisher = "Cambridge University Press",
number = "1",

}

Download

TY - JOUR

T1 - Monte Carlo Algorithms for Finding the Maximum of a Random Walk with Negative Drift

AU - Baringhaus, Ludwig

AU - Grübel, Rudolf

PY - 2006

Y1 - 2006

N2 - We discuss two Monte Carlo algorithms for finding the global maximum of a simple random walk with negative drift. This problem can be used to connect the analysis of random input Monte Carlo algorithms with ideas and principles from mathematical statistics.

AB - We discuss two Monte Carlo algorithms for finding the global maximum of a simple random walk with negative drift. This problem can be used to connect the analysis of random input Monte Carlo algorithms with ideas and principles from mathematical statistics.

KW - Brownian motion with drift

KW - Conditioning

KW - Efficiency

KW - Fast Fourier transform

KW - Ladder variable

KW - Markov chain

KW - Randomization

UR - http://www.scopus.com/inward/record.url?scp=33845330886&partnerID=8YFLogxK

U2 - 10.1239/jap/1143936244

DO - 10.1239/jap/1143936244

M3 - Article

AN - SCOPUS:33845330886

VL - 43

SP - 74

EP - 86

JO - Journal of Applied Probability

JF - Journal of Applied Probability

SN - 0021-9002

IS - 1

ER -