On exponential bounds for the waiting-time distribution function in GI/G/1

1976 ◽  
Vol 13 (2) ◽  
pp. 411-417 ◽  
Author(s):  
R. Bergmann ◽  
D. Stoyan
Keyword(s):  
Distribution Function ◽  
Waiting Time ◽  
Time Distribution ◽  
Arrival Time ◽  
Distribution Functions ◽  
Integral Inequalities ◽  
Arrival Time Distribution ◽  
Waiting Time Distribution ◽  
Exponential Bounds ◽  
Stationary Waiting Time

Exponential bounds for the stationary waiting-time distribution of the type ae–θt are considered. These bounds are obtained by the use of Kingman's method of ‘integral inequalities’. Approximations of Θ and a are given which are useful especially if the service and/or inter-arrival time distribution functions are NBUE or NWUE.

On exponential bounds for the waiting-time distribution function in GI/G/1

1976 ◽  
Vol 13 (02) ◽  
pp. 411-417
Author(s):  
R. Bergmann ◽  
D. Stoyan
Keyword(s):  
Distribution Function ◽  
Waiting Time ◽  
Time Distribution ◽  
Arrival Time ◽  
Distribution Functions ◽  
Integral Inequalities ◽  
Arrival Time Distribution ◽  
Waiting Time Distribution ◽  
Exponential Bounds ◽  
Stationary Waiting Time

Exponential bounds for the stationary waiting-time distribution of the type ae–θt are considered. These bounds are obtained by the use of Kingman's method of ‘integral inequalities’. Approximations of Θ and a are given which are useful especially if the service and/or inter-arrival time distribution functions are NBUE or NWUE.

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.

SPECTRUM OF COSMIC RAYS WITH ENERGY ABOVE 1017 EV

2005 ◽  
Vol 20 (29) ◽  
pp. 6878-6880 ◽  
Author(s):  
V. P. EGOROVA ◽  
A. V. GLUSHKOV ◽  
A. A. IVANOV ◽  
S. P. KNURENKO ◽  
V. A. KOLOSOV ◽  
...  
Keyword(s):  
Distribution Function ◽  
Energy Spectrum ◽  
Cosmic Rays ◽  
Time Distribution ◽  
Arrival Time ◽  
Lateral Distribution ◽  
Arrival Time Distribution ◽  
Array Data ◽  
Lateral Distribution Function ◽  
High Energies

The energy spectrum of primary cosmic rays with ultra-high energies based on the Yakutsk EAS Array data is presented. For the largest events values of S600 and axis coordinates have been obtained using revised lateral distribution function. The effect of the arrival time distribution at several axis distance on estimated density for Yakutsk and AGASA is considered.

Another martingale bound on the waiting-time distribution in GI/G/1 queues

1979 ◽  
Vol 16 (2) ◽  
pp. 454-457 ◽  
Author(s):  
Harry H. Tan
Keyword(s):  
Waiting Time ◽  
Upper Bound ◽  
Time Distribution ◽  
Waiting Time Distribution ◽  
Martingale Approach ◽  
Stationary Waiting Time

A new upper bound on the stationary waiting-time distribution of a GI/G/1 queue is derived following Kingman's martingale approach. This bound is generally stronger than Kingman's upper bound and is sometimes stronger than an upper bound derived by Ross.

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