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A Dirty Model for Multiple Sparse Regression
Terms—Multi-task Learning High-dimensional Statistics
2011/7/7
Sparse linear regression -- finding an unknown vector from linear measurements -- is now known to be possible with fewer samples than variables, via methods like the LASSO. We consider the multiple sp...
Consistency of maximum-likelihood and variational estimators in the Stochastic Block Model
maximum-likelihood Stochastic Block Model
2011/6/17
The stochastic block model (SBM) is a probabilistic model de-
signed to describe heterogeneous directed and undirected graphs. In this
paper, we address the asymptotic inference on SBM by use of max...
A Dynamic Spatio-temporal Precipitation Model
Rainfall modeling Space-time model Bayesian hierarchical model Markov chain Monte Carlo (MCMC) method Censoring Gaussian random fi eld
2011/3/24
A spatio-temporal model for precipitation is presented. Modeling the continuous and the discrete part of rainfall together, it is assumed that precipitation has a censored and power-transformed normal...
A Dynamic Spatio-temporal Precipitation Model
Rainfall modeling Space-time model Bayesian hierarchical model Markov chain Monte Carlo (MCMC) method Censoring Gaussian random fi eld
2011/3/24
A spatio-temporal model for precipitation is presented. Modeling the continuous and the discrete part of rainfall together, it is assumed that precipitation has a censored and power-transformed normal...
A Dynamic Spatio-temporal Precipitation Model
Rainfall modeling Space-time model Bayesian hierarchical model Markov chain Monte Carlo (MCMC) method Censoring Gaussian random fi eld
2011/3/23
A spatio-temporal model for precipitation is presented. Modeling the continuous and the discrete part of rainfall together, it is assumed that precipitation has a censored and power-transformed normal...
Classical regression analysis relates the expectation of a response variable to a linear combination of explanatory variables. In this article, we propose a covariance regression model that parameteri...
Lack of confidence in ABC model choice
Lack of confidence ABC model choice Approximate Bayesian computation
2011/3/24
Approximate Bayesian computation (ABC) have become a essential tool for the analysis of complex stochastic models. Earlier, Grelaud et al. (2009) advocated the use of ABC for Bayesian model choice in ...
A Note on an R^2 Measure for Fixed Effects in the Generalized Linear Mixed Model
Goodness-of-fit Correlated data Model selection Multiple correlation Maximum likelihood Nonnormal distribution
2010/11/8
Using the LRT statistic, a model V# is proposed for the generalized linear mixed model for
assessing the association between the correlated outcomes and fixed effects. The V# compares
the full model...
A factor mixture analysis model for multivariate binary data
model based clustering latent trait analysis EM algorithm
2010/10/19
The paper proposes a latent variable model for binary data coming from an unobserved heterogeneous population. The heterogeneity is taken into account by replacing the traditional assumption of Gauss...
Sensitivity Analysis to Select the Most Influential Risk Factors in a Logistic Regression Model
Risk Factors Logistic Regression Model
2009/9/3
The traditional variable selection methods for survival data depend on iteration procedures, and control of this process assumes tuning parameters that are problematic and time consuming, especially i...
The Jammed Phase of the Biham-Middleton-Levine Traffic Model
trac phase transition percolation cellular automata
2009/4/24
Initially a car is placed with probability $p$ at each site of the two-dimensional integer lattice. Each car is equally likely to be East-facing or North-facing, and different sites receive independen...
There are two types of particles interacting on a homogeneous tree of degree d+1. The particles of the first type colonize the empty space with exponential rate 1, but cannot take over the vertices th...
A simple fluctuation lower bound for a disordered massless random continuous spin model in d=2
Interfaces quenched systems continuous spin models entropy inequality
2009/4/22
We prove a finite volume lower bound of the order square root of log N on the delocalization of a disordered continuous spin model (resp. effective interface model) in d=2 in a box of size N. The inte...
The volume fraction of a non--overlapping germ--grain model
volume fraction germ-grain model dead leaves model
2009/4/22
We discuss the volume fraction of a model of non--overlapping convex grains. It is obtained from thinning a Poisson process where each point has a weight and is the centre of a grain, by removing any ...