Perfect simulation of a one-dimensional loss network on R with length distribution pi and cable capacity C is performed using the clan of ancestors method. Previous works estimated the region of convergence of this scheme using a domination by a branching process. In this work, we show that the domination by the branching process is far from sharp and that there is room for improvement. Moreover, we derive an empirical relation concerning the critical value using simulation studies on the number of rectangles present in the clan of ancestors.10345346
We present a perfect simulation algorithm for measures that are absolutely continuous with respect t...
Recently Rajasekaran and Ross [1] presented an algorithm that takes an expected 0(1) time to generat...
29 Pages.We prove the existence of the total length process for the genealogical tree of a populatio...
AbstractPerfect simulation of an one-dimensional loss network on R with length distribution π and ca...
AbstractPerfect simulation of an one-dimensional loss network on R with length distribution π and ca...
One dimensional continuous loss networks are spatial birth-and-death processes which can be dominate...
International audienceWe consider a model of stationary population with random size given by a conti...
International audienceWe consider a model of stationary population with random size given by a conti...
Recently Rajasekaran and Ross [1] presented an algorithm that takes an expected 0(1) time to generat...
a. Assume the network grows as described in [1, Fig. 3b], by duplication of a gene (node) chosen uni...
Abstract. We consider the problem of reconstructing a maximally par-simonious history of network evo...
Abstract. We consider the problem of reconstructing a maximally par-simonious history of network evo...
Abstract: For multiservice loss networks the calculation of the normalization constant is computatio...
The ability to simulate networks accurately and efficiently is of growing importance as many aspects...
Recommended by N. Sagias When simulating a wireless network, users/nodes are usually assumed to be d...
We present a perfect simulation algorithm for measures that are absolutely continuous with respect t...
Recently Rajasekaran and Ross [1] presented an algorithm that takes an expected 0(1) time to generat...
29 Pages.We prove the existence of the total length process for the genealogical tree of a populatio...
AbstractPerfect simulation of an one-dimensional loss network on R with length distribution π and ca...
AbstractPerfect simulation of an one-dimensional loss network on R with length distribution π and ca...
One dimensional continuous loss networks are spatial birth-and-death processes which can be dominate...
International audienceWe consider a model of stationary population with random size given by a conti...
International audienceWe consider a model of stationary population with random size given by a conti...
Recently Rajasekaran and Ross [1] presented an algorithm that takes an expected 0(1) time to generat...
a. Assume the network grows as described in [1, Fig. 3b], by duplication of a gene (node) chosen uni...
Abstract. We consider the problem of reconstructing a maximally par-simonious history of network evo...
Abstract. We consider the problem of reconstructing a maximally par-simonious history of network evo...
Abstract: For multiservice loss networks the calculation of the normalization constant is computatio...
The ability to simulate networks accurately and efficiently is of growing importance as many aspects...
Recommended by N. Sagias When simulating a wireless network, users/nodes are usually assumed to be d...
We present a perfect simulation algorithm for measures that are absolutely continuous with respect t...
Recently Rajasekaran and Ross [1] presented an algorithm that takes an expected 0(1) time to generat...
29 Pages.We prove the existence of the total length process for the genealogical tree of a populatio...