搜索结果: 16-30 共查到“贝叶斯统计”相关记录79条 . 查询时间(1.758 秒)
跳跃自激发与非对称交叉回馈机制下的期权定价研究
跳跃自激发行为 非对称交叉回馈机制 序贯贝叶斯参数学习
2018/2/7
跳跃集聚和波动率非对称回馈是股票价格运动过程中不可忽视的重要特征.基于动态跳-扩散半鞅随机过程，本文提出了具有时变跳跃到达率和波动率的双因子交叉回馈机制的期权定价模型，推导了跳-扩散交叉回馈模型的一般化风险中性变换关系；同时借助序贯贝叶斯方法对模型和跳跃风险溢价进行校准，并对道琼斯工业平均指数（DJX）、标普500指数（SPX）、苹果（APL）、IBM、JP摩根（JPM）股票进行实证研究.研究发现...
2018高维统计模型的贝叶斯计算研讨会（Workshop on Bayesian Computation for High-Dimensional Statistical Models）
2018 高维统计模型的贝叶斯计算 研讨会
2017/12/20
In recent years there has been an explosion of complex data-sets in areas as diverse as Bioinformatics, Ecology, Epidemiology, Finance, subsurface Geophysics, Meteorology, and Population genetics. In ...
分布式决策是提高群体自主性的关键技术之一. 以侦查类无人机(unmanned search aerial vehicles, USAV)和 打击类无人机(unmanned combat aerial vehicles, UCAV)执行协同搜索、攻击灰色目标区域问题为背景, 建立了一种 考虑局部链式通信、无人机飞行性能和任务执行能力等多约束的分布式任务分配模型, 基于贝叶斯定理将任务空 间的连续/离...
非参数贝叶斯分析主要是将兴趣参数或潜变量的分布视为随机的并赋予一个先验分布.作为分布函数的分布,Dirichlet过程是目前非参数贝叶斯分析中最受欢迎的先验分布,并受到广泛的关注.本文对近几十年来Dirichlet过程的发展作了一下回顾和总结,并就Dirichlet过程在潜变量模型中的应用做了介绍.
Minimax Risk: Pinsker Bound
COMMUNICATION THEORY, STATISTICAL DENSITY ESTIMATION FISHER INFORMATION KERNEL ESTIMATORS LINEAR ESTIMATORS, BAYES LOCAL ASYMPTOTIC NORMALITY METHOD OF SIEVES MINIMAX ESTIMATION NOISE (SIGNAL PROCESSING IN THE PRESENCE OF ) PREDICTION AND FILTERING LINEAR SIEVES, METHOD OF SPECTRAL ANALYSIS SHRINKAGE ESTIMATORS SMOOTHNESS PRIORS SOBOLEV SPACES SPLINE FUNCTIONS STATIONARY PROCESSES STEIN EFFECT
2015/8/25
We give an account of the Pinsker bound describing the exact asymptotics of the minimax risk in a class of nonparametric smoothing problems. The parameter spaces are Sobolev classes or ellipsoids, and...
Asymptotic Minimaxity of False Discovery Rate Thresholding for Sparse Exponential Data
Minimax Decision theory Minimax Bayes estimation
2015/8/21
Control of the False Discovery Rate (FDR) is a recent innovation in multiple hypothesis
testing, allowing the user to limit the fraction of rejected null hypotheses which correspond to
false rejecti...
The Sentimental Factor:Improving Review Classification via Human-Provided Information
Sentimental Factor Review Classification Human-Provided Information
2015/8/21
Sentiment classification is the task of labeling a review document according to the polarity of its prevailing opinion (favorable or unfavorable). In approaching this problem, a model builder often ha...
Optimal Multiple Testing Under a Gaussian Prior on the Effect Sizes
Effect Sizes Multiple Testing
2015/8/21
We develop a new method for frequentist multiple testing with Bayesian prior information.
Our procedure nds a new set of optimal p-value weights called the Bayes weights. Prior
information is relev...
Bootstrapping data arrays of arbitrary order
Bayesian pigeonhole bootstrap online bagging online bootstrap
2015/8/21
In this paper we study a bootstrap strategy for estimating the variance of a mean taken over large multifactor crossed random e ects data
sets. We apply bootstrap reweighting independently to the lev...
Ideal Denoising in an orthonormal basis chosen from a library of bases
Wavelet Packets Cosine Packets weak-` p spaces
2015/8/20
Suppose we have observations yi = si +zi, i = 1; :::; n, where (si) is signal and (zi)
is i.i.d. Gaussian white noise. Suppose we have available a library L of orthogonal
bases, such as the Wavelet ...
Ideal Spatial Adaptation by Wavelet Shrinkage
Minimax estimation sub ject to doing well at a point Orthogonal Wavelet Bases of Compact Support
2015/8/20
With ideal spatial adaptation, an oracle furnishes information about how best to
adapt a spatially variable estimator, whether piecewise constant, piecewise polynomial,
variable knot spline, or vari...
Consider estimating the mean vector from data Nn(; 2I ) with lq norm loss,
q 1, when is known to lie in an n-dimensional lp ball, p 2 (0; 1). For large
n, the ratio of minimax linear risk to...
On minimax estimation of a sparse normal mean vector
nearly black object robustness white noise model
2015/8/20
Mallows has conjectured that among distributions which are Gaussian but
for occasional contamination by additive noise, the one having least Fisher
information has (two-sided) geometric contaminatio...
Minimax Bayes, asymptotic minimax and sparse wavelet priors
Minimax Decision theory Minimax Bayes estimation
2015/8/20
Pinsker(1980) gave a precise asymptotic evaluation of the minimax mean squared
error of estimation of a signal in Gaussian noise when the signal is known a priori
to lie in a compact ellipsoid in Hi...