Avancerad sökning
Visar resultat 1 - 5 av 39 avhandlingar som matchar ovanstående sökkriterier.
1. Semi Markov chain Monte Carlo
Sammanfattning : The first paper introduces a new simulation technique, called semi Markov chain Monte Carlo, suitable for estimating the expectation of a fixed function over a distribution π, Eπf(χ). Given a Markov chain with stationary distribution p, for example a Markov chain corresponding to a Markov chain Monte Carlo algorithm, an embedded Markov renewal process is used to divide the trajectory into different parts. LÄS MER
2. Case studies in omniparametric simulation
Sammanfattning : In the eld of particle systems and growths models simulation is an important tool. When explicit calculations are too complex or impossible to perform we may use simulations instead. We adapt a new technique here denoted omniparametric simulation, to the two-type Richardson, Ising and Potts models. LÄS MER
3. On Perfect Simulation of Markovian Queueing Networks with Blocking
Sammanfattning : Perfect simulation of a class of Markovian queueing networks with finite buffers is examined in this monograph. The network processes defined are modelled by restricted multivariate birth and death processes with intensities depending on a random environment. The random environments are mainly a set of independent onoff processes. LÄS MER
4. Rare-event simulation with Markov chain Monte Carlo
Sammanfattning : Stochastic simulation is a popular method for computing probabilities or expecta- tions where analytical answers are difficult to derive. It is well known that standard methods of simulation are inefficient for computing rare-event probabilities and there- fore more advanced methods are needed to those problems. LÄS MER
5. On perfect simulation and EM estimation
Sammanfattning : Perfect simulation and the EM algorithm are the main topics in this thesis. In paper I, we present coupling from the past (CFTP) algorithms that generate perfectly distributed samples from the multi-type Widom--Rowlin-son (W--R) model and some generalizations of it. LÄS MER