Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Kengo Kamatani"'
Autor:
Alexandre Brouste, Masaaki Fukasawa, Hideitsu Hino, Stefano Iacus, Kengo Kamatani, Yuta Koike, Hiroki Masuda, Ryosuke Nomura, Teppei Ogihara, Yasutaka Shimuzu, Masayuki Uchida, Nakahiro Yoshida
Publikováno v:
Journal of Statistical Software, Vol 57, Iss 1, Pp 1-51 (2014)
The YUIMA Project is an open source and collaborative effort aimed at developing the R package yuima for simulation and inference of stochastic differential equations. In the yuima package stochastic differential equations can be of very abstract typ
Externí odkaz:
https://doaj.org/article/7bc6d5ad145b444f9f69e9a8d83e7c7c
Autor:
Kengo Kamatani
Publikováno v:
Stochastic Processes and their Applications. 130:297-327
High-dimensional asymptotics of the random walk Metropolis–Hastings algorithm are well understood for a class of light-tailed target distributions. Although this idealistic assumption is instructive, it may not always be appropriate, especially for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c920d27d89d52b4a7dfc3a7ee9ee02e6
https://doi.org/10.1016/j.spa.2019.03.002
https://doi.org/10.1016/j.spa.2019.03.002
Publikováno v:
Journal of Japan Society of Civil Engineers, Ser. A1 (Structural Engineering & Earthquake Engineering (SE/EE)). 75:88-94
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::297436268d30baf71198471ce40155f4
https://doi.org/10.2208/jscejseee.75.88
https://doi.org/10.2208/jscejseee.75.88
Autor:
Kengo KAMATANI, Xiaolin SONG
Recently, many Markov chain Monte Carlo methods have been developed with deterministic reversible transform proposals inspired by the Hamiltonian Monte Carlo method. The deterministic transform is relatively easy to reconcile with the local informati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d568a70951d8317f7eb35d9a419d9d21
Autor:
Kengo Kamatani, Xiaolin Song
We construct a class of non-reversible Metropolis kernels as a multivariate extension of the guided-walk kernel proposed by Gustafson 1998. The main idea of our method is to introduce a projection that maps a state space to a totally ordered group. B
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd0a431e2d1fe211455bf6e897d1768b
http://arxiv.org/abs/2005.05584
http://arxiv.org/abs/2005.05584
Bayesian inference for stable Lévy–driven stochastic differential equations with high‐frequency data
Publikováno v:
Scandinavian Journal of Statistics. 46:545-574
In this article we consider parametric Bayesian inference for stochastic differential equations (SDE) driven by a pure-jump stable Levy process, which is observed at high frequency. In most cases of practical interest, the likelihood function is not
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e817fa18ab868f29a698971784deb9e
https://doi.org/10.1111/sjos.12362
https://doi.org/10.1111/sjos.12362
Publikováno v:
International Journal for Uncertainty Quantification. 8:61-73
In this article we consider computing expectations w.r.t.~probability laws associated to a certain class of stochastic systems. In order to achieve such a task, one must not only resort to numerical approximation of the expectation, but also to a bia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0bbdc33bf85fa2dd9c31013c993ee6ff
https://doi.org/10.1615/int.j.uncertaintyquantification.2018021551
https://doi.org/10.1615/int.j.uncertaintyquantification.2018021551
Publikováno v:
Advances in Applied Probability. 49:24-48
We consider the numerical approximation of the filtering problem in high dimensions, that is, when the hidden state lies in ℝd with large d. For low-dimensional problems, one of the most popular numerical procedures for consistent inference is the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f42adea1da4657b284619f0629058c4d
https://doi.org/10.1017/apr.2016.77
https://doi.org/10.1017/apr.2016.77
Publikováno v:
Bulletin of informatics and cybernetics. 48:19-35
We deal with an estimation problem of a volatility parameter for stochastic regression models based on high frequency data. Hybrid multi-step estimators are proposed and their asymptotic properties, including convergence of moments, are obtained.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7aff00309191eec9cc2ed2e24a61ab6e
http://hdl.handle.net/2324/2203025
http://hdl.handle.net/2324/2203025
Publikováno v:
Statistics and Computing. 28:47-60
In this article we introduce two new estimates of the normalizing constant (or marginal likelihood) for partially observed diffusion (POD) processes, with discrete observations. One estimate is biased but non-negative and the other is unbiased but no
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d2133ae655237fde0a5a7deb8a6737aa
https://doi.org/10.1007/s11222-016-9715-5
https://doi.org/10.1007/s11222-016-9715-5