搜索结果: 1-13 共查到“应用统计数学 models”相关记录13条 . 查询时间(0.25 秒)
Non-Asymptotic Analysis of Adaptive and Annealed Feynman-Kac Particle Models
Feynman-Kacmodels interacting particle systems adaptive models
2012/11/26
Sequential and Quantum Monte Carlo methods, as well as genetic type search algorithms can be interpreted as a mean field and interacting particle approximations of Feynman-Kac models in distribution s...
The importance of distinct modeling strategies for gene and gene-specific treatment effects in hierarchical models for microarray data
Diffierential expression EM algorithm hierarchical models random effects uncertainty
2012/11/23
When analyzing microarray data, hierarchical models are often used to share information across genes when estimating means and variances or identifying differential expression. Many methods utilize so...
Functional dynamic factor models with application to yield curve forecasting
Functional data analysis expectation maximization algorithm natural cubic splines cross-validation roughness penalty
2012/11/23
Accurate forecasting of zero coupon bond yields for a continuum of maturities is paramount to bond portfolio management and derivative security pricing. Yet a universal model for yield curve forecasti...
Probabilistic Auto-Associative Models and Semi-Linear PCA
Probabilistic Auto-Associative Models Semi-Linear PCA
2012/11/22
Auto-Associative models cover a large class of methods used in data analysis. In this paper, we describe the generals properties of these models when the projection component is linear and we propose ...
Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors
Group descent algorithms nonconvex penalized linear model logistic regression model grouped predictors
2012/11/22
Penalized regression is an attractive framework for variable selection problems. Often, variables possess a grouping structure, and the relevant selection problem is that of selecting groups, not indi...
Simple techniques for likelihood analysis of univariate and multivariate stable distributions: with extensions to multivariate stochastic volatility and dynamic factor models
Univariate and multivariatestable distributions MCMC Approximate,Aayesian,Computation Characteristic function
2012/11/21
In this paper we consider a variety of procedures for numerical statistical inference in the family of univariate and multivariate stable distributions. In connection with univariate distributions (i)...
Marginal Likelihood Computation for Hidden Markov Models via Generalized Two-Filter Smoothing
MarginalLikelihood Sequential MonteCarlo Generalized Two-Filter Smoothing
2012/11/21
In this note we introduce an estimate for the marginal likelihood associated to hidden Markov models (HMMs) using sequential Monte Carlo (SMC) approximations of the generalized two-filter smoothing de...
Fitting directed acyclic graphs with latent nodes as finite mixtures models, with application to education transmission
Extendedlatentclassmodels mixturemodels structuralequations causal inference
2012/11/22
This paper describes an efficient EM algorithm for maximum likelihood estimation of a system of nonlinear structural equations corresponding to a directed acyclic graph model that can contain an arbit...
Bayesian variable selection for spatially dependent generalized linear models
generalized linear models variable selection Bayesian spatially
2012/11/22
Despite the abundance of methods for variable selection and accommodating spatial structure in regression models, there is little precedent for incorporating spatial dependence in covariate inclusion ...
Nonparametric estimation in hidden Markov models
Nonparametric estimation hidden Markov models
2012/11/22
This paper outlines a new procedure to perform nonparametric estimation in hidden Markov models. It is assumed that a Markov chain (Xk) is observed only through a process (Yk), where Yk is a noisy obs...
Bayesian inference for nonlinear structural time series models
DSGEmodel Multi-modal Partially adapted particle flter State space
2012/11/21
This article discusses a partially adapted particle filter for estimating the likelihood of a nonlinear structural econometric state space models whose state transition density cannot be expressed in ...
Indifference of Defaultable Bonds with Stochastic Intensity models
Credit Risk model Cox Process HJB equations Indif-ference Pricing Minimal Entropy Measure Finite difference Method
2010/4/27
The utility-based pricing of defaultable bonds in the case of stochastic intensity models of default risk is discussed. The Hamilton-Jacobi- Bellman (HJB) equations for the value functions is derived....
Statistical identification with hidden Markov models of large order splitting strategies in an equity market
Statistical identification hidden Markov models order splitting strategies
2010/4/27
Large trades in a financial market are usually split into smaller parts and traded incrementally over extended periods of time. We address these large trades as hidden orders. In order to identify and...
