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Learning the Structure of Mixed Graphical Models
Learning the Structure Mixed Graphical Models
2015/8/21
We consider the problem of learning the structure of a pairwise graphical model over continuous and discrete variables. We present a new pairwise model for graphical models with both continuous and di...
Mixed State Estimation for a Linear Gaussian Markov Model
Mixed State Estimation Linear Gaussian Markov Model
2015/7/9
We consider a discrete-time dynamical system with Boolean and continuous states, with the continuous state propagating linearly in the continuous and Boolean state variables, and an additive Gaussian ...
Mixed Linear System Estimation and Identification
Statistical estimation Convex relaxation Interior-point methods
2015/7/9
We consider a mixed linear system model, with both continuous and discrete inputs and outputs, described by a coefficient matrix and a set of noise variances. When the discrete inputs and outputs are ...
Large deviation principles and complete equivalence and nonequivalence results for pure and mixed ensembles
Statistics turbulent coherent structures mechanical model the model of two-dimensional fluid motion
2014/12/29
We consider a general class of statistical mechanical models of coherent structures in turbulence, which includes models of two-dimensional fluid motion, quasi-geostrophic flows, and dispersive waves....
Mixed Lefschetz Theorems and Hodge-Riemann Bilinear Relations
Bilinear relation algebra smooth compact Kahler manifolds hodge structure
2014/12/24
The Hard Lefschetz Theorem (HLT) and the Hodge–Riemann bilinear relations (HRR) hold in various contexts: they impose restrictions on the cohomology algebra of a smooth compact Kähler manifold; t...
Review of: Mixed Effects Models and Extensions in Ecology with R
Mixed Effects Models Extensions in Ecology R
2013/6/14
This is a review of the book "Mixed Effects Models and Extensions in Ecology with R" by Zuur, Ieno, Walker, Saveliev and Smith (2009, Springer). I was asked to review this book for The American Statis...
A Penalized Multi-trait Mixed Model for Association Mapping in Pedigree-based GWAS
Multivariate linear mixed model Penalization approach Feature selection 1 arXiv:1305.4413v1 [stat.ME] 19 May 2013 GWAS
2013/6/14
In genome-wide association studies (GWAS), penalization is an important approach for identifying genetic markers associated with trait while mixed model is successful in accounting for a complicated d...
Efficient Algorithms for Multivariate Linear Mixed Models in Genome-wide Association Studies
Efficient Algorithms Multivariate Linear Mixed Models Genome-wide Association Studies
2013/6/17
Multivariate linear mixed models (mvLMMs) have been widely used in many areas of genetics, and have attracted considerable recent interest in genome-wide association studies (GWASs). However, existing...
Scalable Text and Link Analysis with Mixed-Topic Link Models
Document classification Community detection Topic mod-eling Link prediction Stochastic block model
2013/5/2
Many data sets contain rich information about objects, as well as pairwise relations between them. For instance, in networks of websites, scientific papers, and other documents, each node has content ...
The maximum likelihood drift estimator for mixed fractional Brownian motion
mixed fractional Brownian motion maximum likelihood estimator large sample asymptotic
2012/9/18
The paper is concerned with the maximum likelihood estimator (MLE) of the unknown drift parameterθ∈Rin the continuous-time regression model Xt =θt+Bt +BHt,t ∈[0, T] whereBt is the Brownian motion and ...
A stochastic variational framework for fitting and diagnosing generalized linear mixed models
Hierarchical model Identify divergent units Large longitudinal data Non-conjugate model Stochastic approximation Variational Bayes
2012/9/17
Variational Bayes computational methods are attracting increasing in-terest because of their ability to scale to large data sets. Here, application of the
non-conjugate variational message passing (N...
Efficient computation with a linear mixed model on large-scale data sets with applications to genetic studies
Efficient computation a linear mixed model on large-scale data sets applications genetic studies
2012/9/19
Motivated by genome-wide association studies we consider astan-dard linear model with one additional random effect in situations where many predictors have been collected on the same subjects and each...
A note on global Markov properties for mixed graphs
Graphical models separation global Markov property
2011/7/19
Global Markov properties in mixed graphs are usually formulated in terms of the path-oriented m-separation or by use of augmented graphs (similar to moral graphs in the case of directed acyclic graphs...
spikeSlabGAM: Bayesian Variable Selection, Model Choice and Regularization for Generalized Additive Mixed Models in R
MCMC P-splines spike-and-slab prior normal-inverse-gamma
2011/6/20
The R package spikeSlabGAM implements Bayesian variable selection, model choice,
and regularized estimation in (geo-)additive mixed models for Gaussian, binomial, and
Poisson responses. Its purpose ...
On construction of optimal mixed-level supersaturated designs
Coincidence number difference matrix equidistant design in-duced matrix orthogonal array
2011/6/20
Supersaturated design (SSD) has received much recent interest
because of its potential in factor screening experiments. In this pa-
per, we provide equivalent conditions for two columns to be fully
...