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Narrowing the gap on heritability of common disease by direct estimation in case-control GWAS
Narrowing the gap heritability common disease direct estimation case-control GWAS
2013/6/17
One of the major developments in recent years in the search for missing heritability of human phenotypes is the adoption of linear mixed-effects models (LMMs) to estimate heritability due to genetic v...
Exploring wind direction and SO2 concentration by circular-linear density estimation
Circular distributions Circular kernel estimation Circular{linear data Copula.
2012/9/17
The study of environmental problems usually requires the description of variables with di er-ent nature and the assessment of relations between them. In this work, an algorithm for exible estimation o...
Positive Definite $\ell_1$ Penalized Estimation of Large Covariance Matrices
Alternating direction methods Large covariance matrices Matrix norm Positive-de nite estimation Sparsity Soft-thresholding.
2012/9/18
The thresholding covariance estimator has nice asymptotic properties for estimating sparse large covariance matrices, but it often has negative eigenvalues when used in real data analysis. To simultan...
Asymptotically efficient estimation of a scale parameter in Gaussian time series and closed-form expressions for the Fisher information
efficient estimation fractional Brownian motion Fisher information general monotone sequence regular variation slowly varying functions spectral density.
2012/9/18
Mimicking the maximum likelihood estimator, we construct first order Cramer-Rao efficient and explicitly computable estimators for the scale parameterσ2 in the model Zi,n =σn−βXi+Yi, i = 1, . . ...
Penalized estimation in high-dimensional hidden Markov models with state-specific graphical models
HMM Graphical Lasso Universal Regularization Model Selection MMDL Greedy Backwards Pruning Genome Biology Chromatin Modeling
2012/9/17
We consider penalized estimation in hidden Markov models (HMMs) with multi-variate Normal observations. In the moderate-to-large dimensional setting, estimation for HMMs remains challenging in practic...
Simultaneous Model Selection and Estimation for Mean and Association Structures with Clustered Binary Data
association clustered binary data generalized estimating equation logistic regression variable selection
2012/9/17
This paper investigates the property of the penalized estimating equations when both the mean and association structures are modelled. To select variables for the mean and association structures seque...
Composite likelihood estimation of sparse Gaussian graphical models with symmetry
Variable selection model selection penalized estimation Gaussian graphical model concentration matrix partial correlation matrix
2012/9/17
In this article, we discuss the composite likelihood estimation of sparse Gaussian graph-ical models. When there are symmetry constraints on the concentration matrix or partial correlation matrix, the...
Nonconcave penalized composite conditional likelihood estimation of sparse Ising models
Composite likelihood coordinatewise optimization Ising model minorization–maximization principle NP-dimension asymptotic theory HIV drug resistance database.
2012/9/17
The Ising model is a useful tool for studying complex interactions within a system. The estimation of such a model, however, is rather challenging, especially in the presence of high-dimensional param...
Test for bandedness of high-dimensional covariance matrices and bandwidth estimation
Banded covariance matrix bandwidth estimation high data dimension largep, small n nonparametric.
2012/9/17
Motivated by the latest effort to employ banded matrices to esti-mate a high-dimensional covariance Σ, we propose a test for Σbeing banded with possible diverging bandwidth. The test is adaptive to th...
Adaptive estimation in regression and complexity of approximation of random fields
regression and complexity approximation random fields
2012/9/17
In this thesis we study adaptive nonparametric regression with noise misspecifi-cation and the complexity of approximation of random fields in dependence of the dimension.
First, we consider the prob...
A note on estimation in Hilbertian linear models
Adaptive estimation consistency functional regression Hilbert spaces infinite-dimensional data.
2012/9/17
We study estimation of the operator in the linear modelY = (X) +", when XandY take values in Hilbert spacesH1 andH2, respectively. Our main objective is to obtain consistency without imposing some rat...
PAC-Bayesian Estimation and Prediction in Sparse Additive Models
Additive models sparsity regression estimation PAC-Bayesian bounds oracle inequality MCMC stochastic search.
2012/9/17
The present paper is about estimation and prediction in high-dimensional additive models under a sparsity assumption (p nparadigm).A PAC-Bayesian strategy is investigated, delivering oracle inequaliti...
Tangent space estimation for smooth embeddings of Riemannian manifolds
Riemannian manifolds tangent space estimation manifold sampling manifold learning Chernoff bounds for sums of random matrices singular value perturbation.
2012/9/17
Numerous dimensionality reduction problems in data analysis involve the recovery of low-dimensional models or the learning of manifolds underlying sets of data. Many manifold learning methods require ...
Sequential Estimation Methods from Inclusion Principle
Sequential Estimation Methods Inclusion Principle
2012/9/17
In this paper, we propose new sequential estimation methodsbased on inclusion principle. The main idea is to reformulate the estimation problems as constructing sequential random intervals and use con...
Re-Weighted l_1 Dynamic Filtering for Time-Varying Sparse Signal Estimation
Re-Weighted Dynamic Filtering Time-Varying Signal Estimation
2012/9/17
Signal estimation from incomplete observations improves as more signal structure can be exploited in the inference process. Classic algorithms (e.g., Kalman filtering) have exploited strong dynamic st...