The Weak Convergence Theorem for the Distribution of the Maximum of a Gaussian Random Walk and Approximation Formulas for its Moments

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Atıf İçin Kopyala

Gokpmar F., Khaniyev T., Mammadova Z.

METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY, cilt.15, sa.2, ss.333-347, 2013 (SCI-Expanded)

• Yayın Türü: Makale / Tam Makale
• Cilt numarası: 15 Sayı: 2
• Basım Tarihi: 2013
• Doi Numarası: 10.1007/s11009-011-9240-0
• Dergi Adı: METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY
• Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
• Sayfa Sayıları: ss.333-347
• Gazi Üniversitesi Adresli: Evet

Özet

In this study, asymptotic expansions of the moments of the maximum (M(beta)) of Gaussian random walk with negative drift ( -aEuro parts per thousand beta), beta > 0, are established by using Bell Polynomials. In addition, the weak convergence theorem for the distribution of the random variable Y(beta) a parts per thousand aEuro parts per thousand 2 beta M(beta) is proved, and the explicit form of the limit distribution is derived. Moreover, the approximation formulas for the first four moments of the maximum of a Gaussian random walk are obtained for the parameter beta aaEuro parts per thousand(0.5, 3.2] using meta-modeling.