Bayesian Graphical Lasso Models and Efficient Posterior Computation

نویسندگان

چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Efficient Computation of `1 Regularized Estimates in Gaussian Graphical Models

In this article, I propose an efficient algorithm to compute `1 regularized maximum likelihood estimates in the Gaussian graphical model. These estimators, recently proposed in an earlier article by Yuan and Lin, conduct parameter estimation and model selection simultaneously and have been shown to enjoy nice properties in both large and finite samples. To compute the estimates, however, can be...

متن کامل

Efficient Bayesian inference for harmonic models via adaptive posterior factorization

Harmonic sinusoidal models are an essential tool for music audio signal analysis. Bayesian harmonic models are particularly interesting, since they allow the joint exploitation of various priors on the model parameters. However existing inference methods often rely on specific prior distributions and remain computationally demanding for realistic data. In this article, we investigate a generic ...

متن کامل

Bayesian lasso for semiparametric structural equation models.

There has been great interest in developing nonlinear structural equation models and associated statistical inference procedures, including estimation and model selection methods. In this paper a general semiparametric structural equation model (SSEM) is developed in which the structural equation is composed of nonparametric functions of exogenous latent variables and fixed covariates on a set ...

متن کامل

Applications of the lasso and grouped lasso to the estimation of sparse graphical models

We propose several methods for estimating edge-sparse and nodesparse graphical models based on lasso and grouped lasso penalties. We develop efficient algorithms for fitting these models when the numbers of nodes and potential edges are large. We compare them to competing methods including the graphical lasso and SPACE (Peng, Wang, Zhou & Zhu 2008). Surprisingly, we find that for edge selection...

متن کامل

Fused Multiple Graphical Lasso

In this paper, we consider the problem of estimating multiple graphical models simultaneously using the fused lasso penalty, which encourages adjacent graphs to share similar structures. A motivating example is the analysis of brain networks of Alzheimer’s disease using neuroimaging data. Specifically, we may wish to estimate a brain network for the normal controls (NC), a brain network for the...

متن کامل

ذخیره 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: 2012

ISSN: 1936-0975

DOI: 10.1214/12-ba729