Asymptotic behavior of the dwell time distribution for a random walk on a positive semi-axis

1974 ◽  
Vol 15 (4) ◽  
pp. 362-366
Author(s):  
A. T. Semenov
Keyword(s):  
Asymptotic Behavior ◽  
Random Walk ◽  
Time Distribution ◽  
Dwell Time

CONTINUOUS-TIME FINANCE AND THE WAITING TIME DISTRIBUTION: MULTIPLE CHARACTERISTIC TIMES

2012 ◽  
Vol 26 (23) ◽  
pp. 1250151 ◽  
Author(s):  
KWOK SAU FA
Keyword(s):  
Distribution Function ◽  
Random Walk ◽  
Waiting Time ◽  
Continuous Time ◽  
Probability Distribution Function ◽  
Time Distribution ◽  
Waiting Time Distribution ◽  
Exponential Functions ◽  
Multiple Characteristic ◽  
Sum Of Products

In this paper, we model the tick-by-tick dynamics of markets by using the continuous-time random walk (CTRW) model. We employ a sum of products of power law and stretched exponential functions for the waiting time probability distribution function; this function can fit well the waiting time distribution for BUND futures traded at LIFFE in 1997.

On the number of times where a simple random walk reaches its maximum

1992 ◽  
Vol 29 (02) ◽  
pp. 305-312 ◽  
Author(s):  
W. Katzenbeisser ◽  
W. Panny
Keyword(s):  
Asymptotic Behavior ◽  
Random Walk ◽  
Random Walks ◽  
Simple Random Walk ◽  
Probability And Statistics

Let Qn denote the number of times where a simple random walk reaches its maximum, where the random walk starts at the origin and returns to the origin after 2n steps. Such random walks play an important role in probability and statistics. In this paper the distribution and the moments of Qn , are considered and their asymptotic behavior is studied.

scholarly journals RNA polymerase motors: dwell time distribution, velocity and dynamical phases

2009 ◽  
Vol 2009 (08) ◽  
pp. P08018 ◽  
Author(s):  
Tripti Tripathi ◽  
Gunter M Schütz ◽  
Debashish Chowdhury
Keyword(s):  
Rna Polymerase ◽  
Time Distribution ◽  
Dwell Time

scholarly journals Anomalous protein kinetics on low-fouling surfaces

2020 ◽  
Vol 22 (9) ◽  
pp. 5264-5271
Author(s):  
Mohammadhasan Hedayati ◽  
Matt J. Kipper ◽  
Diego Krapf
Keyword(s):  
Bovine Serum Albumin ◽  
Serum Albumin ◽  
Single Molecule ◽  
Bovine Serum ◽  
Time Distribution ◽  
Dwell Time ◽  
Protein Kinetics ◽  
Single Molecule Tracking ◽  
Heavy Tailed ◽  
Protein Bovine Serum Albumin

Single-molecule tracking reveals the protein bovine serum albumin exhibits anomalous kinetics with a heavy-tailed dwell time distribution on PEG surfaces. This effect is shown to be caused by the ability of the protein to oligomerize in solution.

Joint asymptotic behavior of local and occupation times of random walk in higher dimension

2007 ◽  
Vol 44 (4) ◽  
pp. 535-563 ◽  
Author(s):  
Endre Csáki ◽  
Antónia Földes ◽  
Pál Révész
Keyword(s):  
Asymptotic Behavior ◽  
Random Walk ◽  
Unit Ball ◽  
Local Time ◽  
Occupation Time ◽  
Local Times ◽  
Higher Dimension ◽  
Occupation Times ◽  
Symmetric Random Walk

Considering a simple symmetric random walk in dimension d ≧ 3, we study the almost sure joint asymptotic behavior of two objects: first the local times of a pair of neighboring points, then the local time of a point and the occupation time of the surface of the unit ball around it.

Winding angle and maximum winding angle of the two-dimensional random walk

1991 ◽  
Vol 28 (4) ◽  
pp. 717-726 ◽  
Author(s):  
Claude Bélisle ◽  
Julian Faraway
Keyword(s):  
Asymptotic Behavior ◽  
Brownian Motion ◽  
Random Walk ◽  
Random Walks ◽  
Computer Simulations ◽  
Asymptotic Distributions ◽  
Two Dimensional ◽  
Exact Distributions ◽  
The Difference ◽  
Winding Angle

Recent results on the winding angle of the ordinary two-dimensional random walk on the integer lattice are reviewed. The difference between the Brownian motion winding angle and the random walk winding angle is discussed. Other functionals of the random walk, such as the maximum winding angle, are also considered and new results on their asymptotic behavior, as the number of steps increases, are presented. Results of computer simulations are presented, indicating how well the asymptotic distributions fit the exact distributions for random walks with 10m steps, for m = 2, 3, 4, 5, 6, 7.

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