about
Current approaches used in epidemiologic studies to examine short-term multipollutant air pollution exposures.Variable selection in strong hierarchical semiparametric models for longitudinal data.Tutorial in biostatistics: data-driven subgroup identification and analysis in clinical trials.Protocolized Care for Early Septic Shock (ProCESS) statistical analysis plan.The identification of complex interactions in epidemiology and toxicology: a simulation study of boosted regression treesIntegrative analysis of gene-environment interactions under a multi-response partially linear varying coefficient modelBinge alcohol alters exercise-driven neuroplasticity.Bayesian variable selection for hierarchical gene-environment and gene-gene interactions.A screening-testing approach for detecting gene-environment interactions using sequential penalized and unpenalized multiple logistic regressionIdentifying gene-environment and gene-gene interactions using a progressive penalization approachRegularized group regression methods for genomic prediction: Bridge, MCP, SCAD, group bridge, group lasso, sparse group lasso, group MCP and group SCAD.Model selection emphasises the importance of non-chromosomal information in genetic studiesComprehensible Predictive Modeling Using Regularized Logistic Regression and Comorbidity Based Features.Regularized logistic regression with network-based pairwise interaction for biomarker identification in breast cancer.Generalized Hierarchical Sparse Model for Arbitrary-Order Interactive Antigenic Sites Identification in Flu Virus Data.Uncovering direct and indirect molecular determinants of chromatin loops using a computational integrative approach.Learning interactions via hierarchical group-lasso regularization.A penalized robust semiparametric approach for gene-environment interactionsIdentification of gene-environment interactions in cancer studies using penalization.Hierarchical interactions model for predicting Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) conversionDetection of gene-environment interactions in a family-based population using SCAD.Accommodating missingness in environmental measurements in gene-environment interaction analysis.Convex Modeling of Interactions with Strong Heredity.Convex Banding of the Covariance Matrix.Identification of biomarker-by-treatment interactions in randomized clinical trials with survival outcomes and high-dimensional spaces.Bayesian Variable Selection on Model Spaces Constrained by Heredity ConditionsSparse estimation of gene-gene interactions in prediction models.Case-only approach to identifying markers predicting treatment effects on the relative risk scale.A Modified Adaptive Lasso for Identifying Interactions in the Cox Model with the Heredity Constraint.Data Shared Lasso: A Novel Tool to Discover UpliftAn Efficient Nonlinear Regression Approach for Genome-wide Detection of Marginal and Interacting Genetic Variations.Weibull regression with Bayesian variable selection to identify prognostic tumour markers of breast cancer survival.Structured detection of interactions with the directed lasso.Risk prediction for heterogeneous populations with application to hospital admission prediction.Identifying gene-gene interactions using penalized tensor regression.Dissecting gene-environment interactions: A penalized robust approach accounting for hierarchical structures.Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting.Sex differences in the impact of acute stroke treatment in a population-based study: a sex-specific propensity score approach.Variance Component Selection With Applications to Microbiome Taxonomic Data.Using the EM algorithm for Bayesian variable selection in logistic regression models with related covariates.
P2860
Q30239874-95786CFD-053A-4140-A28A-967481F925DCQ31076779-1CB0EA0A-3462-41F6-9DEB-3DA1B1FD5B75Q31119441-1DC20E2F-7A37-4A82-B733-2E44FA0E491FQ33844701-E90B2CF2-1275-4888-92B5-B2F6ED58356BQ33997754-9291E510-9C37-4F0A-A6DB-1030D942B15CQ34475588-6EED8C53-2C51-4C7F-8275-BC5B422283D3Q34680228-829DE2C9-A08C-46AE-BADE-0B47EEA55067Q34810635-52F40958-2D17-4608-A56F-934BD06F9D47Q34988246-BE0EB7F5-DAE0-4163-9916-3E553939ABF6Q35167216-820FD810-DABF-471E-91DF-7A9C94072032Q35528779-05F535D1-BBE7-44EE-B20C-23C98ABA050FQ35549963-1C3334C6-603C-4096-930D-8BE762ED49FDQ35863025-046FBC8A-5846-461E-B866-69877D28C203Q35937992-EF771540-C23C-4709-B7B7-9567A3BD066CQ36341548-09B1D07D-A5A4-445B-9480-41FBFDF33BB0Q36380044-A514FE5C-A19C-4D11-AF66-04F63436090CQ36446528-0D3A044C-4A70-4B93-A2B6-CC08E2B65B0BQ36469955-EB25D969-275A-4B33-852D-4CCE19F9B700Q37407232-5245A553-C5DB-4EFE-BCD7-7070A70C537CQ37451840-FAAD3715-AE3B-4207-971C-7B8990C69FA9Q38679643-43C95D84-ED51-4917-98B7-824A9B958A50Q38705392-56C1496C-0342-473F-A601-570DA069954FQ38895787-0A28DFB1-34B0-41A7-9567-CD1B3E7BB29DQ39044841-795CD7F4-3178-4E0D-803A-78C8FD55B11DQ39175273-25B69C3F-7A5B-4894-812C-A79FDE13CB2FQ41065835-72001CF7-73D7-4EA5-9727-BAFF24C599D4Q41490600-AC4CC536-4F06-4CCA-97F1-04F9918B109AQ41993145-D13F7DF5-CD72-49D1-9E12-FF2A5B724CCBQ42117800-A4CFE93A-08A2-43C9-9769-71D0C93CBB0EQ42698240-3F581D64-90DE-4104-AC17-109232F6953BQ42769554-346BB4D1-3192-4429-A6AE-7F92D6932629Q43530466-08A31033-2272-4BE1-9661-4B33FC4537B8Q47225682-862D2ACF-B3A7-484A-B28E-4B38B5DA27F0Q47311232-D2EBBC87-7C81-4DA8-BBDC-C97AC1509A18Q47649108-8E01EC12-2CF7-4379-BA7E-9E3826D29352Q47789970-4A8F145B-6AB8-4F97-968F-E7E19A1E22EFQ49905853-181FCBB7-E8AF-4860-BBAC-15BCA38AD5EAQ49958817-33BF2149-6F02-4D5E-B54A-28F92C476CFDQ54237360-CA157304-C917-4CD6-B5CA-31EFE3EB0A95Q55081482-7B154AC0-A77D-4B3F-9A44-E881FBA93C11
P2860
description
2013 nî lūn-bûn
@nan
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
2013年论文
@zh
2013年论文
@zh-cn
name
A LASSO FOR HIERARCHICAL INTERACTIONS.
@ast
A LASSO FOR HIERARCHICAL INTERACTIONS.
@en
type
label
A LASSO FOR HIERARCHICAL INTERACTIONS.
@ast
A LASSO FOR HIERARCHICAL INTERACTIONS.
@en
prefLabel
A LASSO FOR HIERARCHICAL INTERACTIONS.
@ast
A LASSO FOR HIERARCHICAL INTERACTIONS.
@en
P2860
P356
P1433
P1476
A LASSO FOR HIERARCHICAL INTERACTIONS.
@en
P2093
Jacob Bien
Jonathan Taylor
P2860
P304
P356
10.1214/13-AOS1096
P577
2013-06-01T00:00:00Z