Likelihood Inference For Diffusions
Likelihood Inference for Diffusions is a statistical methodology for estimating parameters of diffusion processes by maximizing the likelihood function derived from the transition density of the stochastic differential equation governing the diffusion, distinguished from alternative inference techniques by its reliance on the exact or approximated probability distribution of the continuous-time process over discrete observations.
29
Publications
1.6K
Citations
48
Authors
53
Institutions
Publications per year
2017–2026
4
Parents
29
Alexandros Beskos, Omiros Papaspiliopoulos, Gareth O. Roberts et al. · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 2006 · 356 citations · Full text
1–5 of 29
48
3
h-index
2
h-index
2
h-index
2
h-index
2
h-index
1–5 of 48
53

University of Warwick
Coventry, United Kingdom
3 h-index
5 publications
196 citations
University of Copenhagen
Copenhagen, Denmark
3 h-index
3 publications
147 citations
Département mathématiques, informatique, sciences de la donnée et technologies du numérique
Castanet-Tolosan, France
2 h-index
2 publications
51 citations
University of Michigan
Ann Arbor, United States
2 h-index
3 publications
45 citations

Universidad Politécnica de Cartagena
Cartagena, Spain
2 h-index
2 publications
89 citations
Université Paris-Sud
Orsay, France
1 h-index
2 publications
66 citations

Delft University of Technology
Delft, The Netherlands
1 h-index
1 publications
56 citations

Imperial College London
London, United Kingdom
1 h-index
1 publications
63 citations
1–8 of 53
Repository · 3 publications · 45 citations
3
h-index
3 publications · 516 citations
3
h-index
3 publications · 197 citations
3
h-index
2 publications · 128 citations
2
h-index
Repository · 2 publications · 54 citations
2
h-index
1–5