Bayesian Adaptive Smoothing Splines Using Stochastic Differential Equations
نویسندگان
چکیده
منابع مشابه
Archimedean copula estimation using Bayesian splines smoothing techniques
Copulas enable to specifymultivariate distributions with givenmarginals.Various parametric proposals weremade in the literature for these quantities, mainly in the bivariate case. They can be systematically derived from multivariate distributions with known marginals, yielding e.g. the normal and the Student copulas. Alternatively, one can restrict his/her interest to a sub-family of copulas na...
متن کاملBayesian Analysis of Multivariate Smoothing Splines
A general version of multivariate smoothing splines with correlated errors and correlated curves is proposed. A suitable symmetric smoothing parameter matrix is introduced, and practical priors are developed for the unknown covariance matrix of the errors and the smoothing parameter matrix. An efficient algorithm for computing the multivariate smoothing spline is derived, which leads to an effi...
متن کاملBayesian Inference in Reducible Stochastic Differential Equations
The linear Ornstein-Ulenbeck diffusion model is too simple to describe the movement of short term interest rates. However diffusions with a non-linear drift and volatility function have no closed form likelihood function which make inference either classical or Bayesian very problematic. A vast range of approximation were proposed in the literature. In this paper, we develop the idea of a non-l...
متن کاملSimulating and Forecasting OPEC Oil Price Using Stochastic Differential Equations
The main purpose of this paper is to provide a quantitative analysis to investigate the behavior of the OPEC oil price. Obtaining the best mathematical equation to describe the price and volatility of oil has a great importance. Stochastic differential equations are one of the best models to determine the oil price, because they include the random factor which can apply the effect of different ...
متن کاملAdaptive Weak Approximation of Stochastic Differential Equations
Adaptive time-stepping methods based on the Monte Carlo Euler method for weak approximation of Itô stochastic differential equations are developed. The main result is new expansions of the computational error, with computable leading-order term in a posteriori form, based on stochastic flows and discrete dual backward problems. The expansions lead to efficient and accurate computation of error ...
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: Bayesian Analysis
سال: 2014
ISSN: 1936-0975
DOI: 10.1214/13-ba866