Bayesian curve fitting for lattice gauge theorists
نویسندگان
چکیده
منابع مشابه
Bayesian curve fitting for lattice gauge theorists
A new method of extracting the low-lying energy spectrum from Monte Carlo estimates of Euclidean-space correlation functions which incorporates Bayesian inference is described and tested. The procedure fully exploits the information present in the correlation functions at small temporal separations and uses this information in a way consistent with fundamental probabilistic hypotheses. The comp...
متن کاملAutomatic Bayesian Curve Fitting
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your perso...
متن کاملA Bayesian Curve Fitting Approach to
A Bayesian method of estimating the power spectra of stationary random processes is proposed. Initially we estimate the true spectra via the log pe-riodogram but due to the inadequacies of the periodogram when the true spectrum has a high dynamic range and/or is rapidly varying for such problems we use the multitaper spectrum estimates which have known error distributions. Piecewise polynomials...
متن کاملBayesian Curve Fitting Using Multivariate Normal Mixtures
Problems of regression smoothing and curve fitting are addressed via predictive inference in a flexible class of mixture models. Multidimensional density estimation using Dirichlet mixture models provides the theoretical basis for semi-parametric regression methods in which fitted regression functions may be deduced as means of conditional predictive distributions. These Bayesian regression fun...
متن کاملBayesian curve fitting using MCMC with applications to signal segmentation
We propose some Bayesian methods to address the problem of fitting a signal modeled by a sequence of piecewise constant linear (in the parameters) regression models, for example, autoregressive or Volterra models. A joint prior distribution is set up over the number of the changepoints/knots, their positions, and over the orders of the linear regression models within each segment if these are u...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Nuclear Physics B - Proceedings Supplements
سال: 2002
ISSN: 0920-5632
DOI: 10.1016/s0920-5632(02)01413-5