Related references
Note: Only part of the references are listed.A note of feature screening via a rank-based coefficient of correlation
Li-Pang Chen
BIOMETRICAL JOURNAL (2023)
Network-Based Discriminant Analysis for Multiclassification
Li-Pang Chen
JOURNAL OF CLASSIFICATION (2022)
Classification and prediction for multi-cancer data with ultrahigh-dimensional gene expressions
Li-Pang Chen
PLOS ONE (2022)
De-noising analysis of noisy data under mixed graphical models
Li-Pang Chen et al.
ELECTRONIC JOURNAL OF STATISTICS (2022)
Semiparametric methods for left-truncated and right-censored survival data with covariate measurement error
Li-Pang Chen et al.
ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS (2021)
Analysis of noisy survival data with graphical proportional hazards measurement error models
Li-Pang Chen et al.
BIOMETRICS (2021)
mgm: Estimating Time-Varying Mixed Graphical Models in High-Dimensional Data
Jonas M. B. Haslbeck et al.
JOURNAL OF STATISTICAL SOFTWARE (2020)
Low Rank and Structured Modeling of High-Dimensional Vector Autoregressions
Sumanta Basu et al.
IEEE TRANSACTIONS ON SIGNAL PROCESSING (2019)
Regularized joint estimation of related vector autoregressive models
A. Skripnikov et al.
COMPUTATIONAL STATISTICS & DATA ANALYSIS (2019)
Integrating gene regulatory pathways into differential network analysis of gene expression data
Tyler Grimes et al.
SCIENTIFIC REPORTS (2019)
Robust estimation of high-dimensional covariance and precision matrices
Marco Avella-Medina et al.
BIOMETRIKA (2018)
Robust precision matrix estimation via weighted median regression with regularization
Hyonho Chun et al.
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE (2018)
Network linear discriminant analysis
Wei Cai et al.
COMPUTATIONAL STATISTICS & DATA ANALYSIS (2018)
High-Dimensional Mixed Graphical Models
Jie Cheng et al.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS (2017)
High dimensional semiparametric latent graphical model for mixed data
Jianqing Fan et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2017)
STRUCTURAL SIMILARITY AND DIFFERENCE TESTING ON MULTIPLE SPARSE GAUSSIAN GRAPHICAL MODELS
Weidong Liu
ANNALS OF STATISTICS (2017)
Sparse Gaussian graphical model estimation via alternating minimization
Onkar Dalal et al.
BIOMETRIKA (2017)
ASYMPTOTICS IN DIRECTED EXPONENTIAL RANDOM GRAPH MODELS WITH AN INCREASING BI-DEGREE SEQUENCE
Ting Yan et al.
ANNALS OF STATISTICS (2016)
Joint estimation of multiple dependent Gaussian graphical models with applications to mouse genomics
Yuying Xie et al.
BIOMETRIKA (2016)
XMRF: an R package to fit Markov Networks to high-throughput genetics data
Ying-Wooi Wan et al.
BMC SYSTEMS BIOLOGY (2016)
Learning the Structure of Mixed Graphical Models
Jason D. Lee et al.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS (2015)
Asymptotic normality in the maximum entropy models on graphs with an increasing number of parameters
Ting Yan et al.
JOURNAL OF MULTIVARIATE ANALYSIS (2015)
Selection and estimation for mixed graphical models
Shizhe Chen et al.
BIOMETRIKA (2015)
A convex pseudolikelihood framework for high dimensional partial correlation estimation with convergence guarantees
Kshitij Khare et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2015)
GEMINI: GRAPH ESTIMATION WITH MATRIX VARIATE NORMAL INSTANCES
Shuheng Zhou
ANNALS OF STATISTICS (2014)
Graphical model selection and estimation for high dimensional tensor data
Shiyuan He et al.
JOURNAL OF MULTIVARIATE ANALYSIS (2014)
The joint graphical lasso for inverse covariance estimation across multiple classes
Patrick Danaher et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2014)
ESTIMATING AND UNDERSTANDING EXPONENTIAL RANDOM GRAPH MODELS
Sourav Chatterjee et al.
ANNALS OF STATISTICS (2013)
Covariate-adjusted precision matrix estimation with an application in genetical genomics
T. Tony Cai et al.
BIOMETRIKA (2013)
A central limit theorem in the β-model for undirected random graphs with a diverging number of vertices
Ting Yan et al.
BIOMETRIKA (2013)
Adjusting for high-dimensional covariates in sparse precision matrix estimation by l1-penalization
Jianxin Yin et al.
JOURNAL OF MULTIVARIATE ANALYSIS (2013)
Condition-number-regularized covariance estimation
Joong-Ho Won et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2013)
Alternating Direction Methods for Latent Variable Gaussian Graphical Model Selection
Shiqian Ma et al.
NEURAL COMPUTATION (2013)
INFERENCE AND CHARACTERIZATION OF MULTI-ATTRIBUTE NETWORKS WITH APPLICATION TO COMPUTATIONAL BIOLOGY
Natallia Katenka et al.
ANNALS OF APPLIED STATISTICS (2012)
LATENT VARIABLE GRAPHICAL MODEL SELECTION VIA CONVEX OPTIMIZATION
Venkat Chandrasekaran et al.
ANNALS OF STATISTICS (2012)
HIGH-DIMENSIONAL SEMIPARAMETRIC GAUSSIAN COPULA GRAPHICAL MODELS
Han Liu et al.
ANNALS OF STATISTICS (2012)
REGULARIZED RANK-BASED ESTIMATION OF HIGH-DIMENSIONAL NONPARANORMAL GRAPHICAL MODELS
Lingzhou Xue et al.
ANNALS OF STATISTICS (2012)
Simultaneous multiple response regression and inverse covariance matrix estimation via penalized Gaussian maximum likelihood
Wonyul Lee et al.
JOURNAL OF MULTIVARIATE ANALYSIS (2012)
Sparse Matrix Graphical Models
Chenlei Leng et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2012)
Sparse Estimation of Conditional Graphical Models With Application to Gene Networks
Bing Li et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2012)
Sparse Nonparametric Graphical Models
John Lafferty et al.
STATISTICAL SCIENCE (2012)
The graphical lasso: New insights and alternatives
Rahul Mazumder et al.
ELECTRONIC JOURNAL OF STATISTICS (2012)
RANDOM GRAPHS WITH A GIVEN DEGREE SEQUENCE
Sourav Chatterjee et al.
ANNALS OF APPLIED PROBABILITY (2011)
A Comprehensive Statistical Model for Cell Signaling
Erdem Yoeruek et al.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2011)
New Insights and Faster Computations for the Graphical Lasso
Daniela M. Witten et al.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS (2011)
A Constrained l1 Minimization Approach to Sparse Precision Matrix Estimation
Tony Cai et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2011)
High-dimensional covariance estimation by minimizing l(1)-penalized log-determinant divergence
Pradeep Ravikumar et al.
ELECTRONIC JOURNAL OF STATISTICS (2011)
HIGH-DIMENSIONAL ISING MODEL SELECTION USING l1-REGULARIZED LOGISTIC REGRESSION
Pradeep Ravikumar et al.
ANNALS OF STATISTICS (2010)
Sparse Multivariate Regression With Covariance Estimation
Adam J. Rothman et al.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS (2010)
Partial Correlation Estimation by Joint Sparse Regression Models
Jie Peng et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2009)
Optimal Experimental Design for Parameter Estimation of a Cell Signaling Model
Samuel Bandara et al.
PLOS COMPUTATIONAL BIOLOGY (2009)
Sparse inverse covariance estimation with the graphical lasso
Jerome Friedman et al.
BIOSTATISTICS (2008)
Model selection and estimation in the Gaussian graphical model
Ming Yuan et al.
BIOMETRIKA (2007)
The adaptive lasso and its oracle properties
Hui Zou
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2006)
Inference in curved exponential family models for networks
David R. Hunter et al.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS (2006)
High-dimensional graphs and variable selection with the Lasso
Nicolai Meinshausen et al.
ANNALS OF STATISTICS (2006)
Causal protein-signaling networks derived from multiparameter single-cell data
K Sachs et al.
SCIENCE (2005)
A gene-expression signature as a predictor of survival in breast cancer.
MJ van de Vijver et al.
NEW ENGLAND JOURNAL OF MEDICINE (2002)
A model for measurement error for gene expression arrays
DM Rocke et al.
JOURNAL OF COMPUTATIONAL BIOLOGY (2001)
Graphical interaction models for multivariate time series
R Dahlhaus
METRIKA (2000)
Share Paper
