Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent [0.03%]
坐标下降法求Cox比例风险模型的正则化路径
Noah Simon,Jerome Friedman,Trevor Hastie et al.
Noah Simon et al.
We introduce a pathwise algorithm for the Cox proportional hazards model, regularized by convex combinations of ℓ1 and ℓ2 penalties (elastic net). Our algorithm fits via cyclical coordinate descent, and employs warm starts to find a solut...
RARtool: A MATLAB Software Package for Designing Response-Adaptive Randomized Clinical Trials with Time-to-Event Outcomes [0.03%]
RARtool：一个用于基于事件发生时间的适应性随机临床试验设计的MATLAB软件包
Yevgen Ryeznik,Oleksandr Sverdlov,Weng Kee Wong
Yevgen Ryeznik
Response-adaptive randomization designs are becoming increasingly popular in clinical trial practice. In this paper, we present RARtool, a user interface software developed in MATLAB for designing response-adaptive randomized comparative cl...
structSSI: Simultaneous and Selective Inference for Grouped or Hierarchically Structured Data [0.03%]
结构化选择性推理用于分组或层次数据中的同时和选择性推断模型
Kris Sankaran,Susan Holmes
Kris Sankaran
The
Kristin A Linn,Eric B Laber,Leonard A Stefanski
Kristin A Linn
Chronic illness treatment strategies must adapt to the evolving health status of the patient receiving treatment. Data-driven dynamic treatment regimes can offer guidance for clinicians and intervention scientists on how to treat patients o...
Regularization Paths for Conditional Logistic Regression: The clogitL1 Package [0.03%]
条件逻辑回归的正则化路径：clogitL1包
Stephen Reid,Rob Tibshirani
Stephen Reid
We apply the cyclic coordinate descent algorithm of Friedman, Hastie, and Tibshirani (2010) to the fitting of a conditional logistic regression model with lasso [Formula: see text] and elastic net penalties. The sequential strong rules of T...
Constructing and Modifying Sequence Statistics for relevent Using informR in [0.03%]
利用informR构建和修改相关序列统计信息
Christopher Steven Marcum,Carter T Butts
Christopher Steven Marcum
The informR package greatly simplifies the analysis of complex event histories in
Nello Blaser,Luisa Salazar Vizcaya,Janne Estill et al.
Nello Blaser et al.
Mathematical models of disease progression predict disease outcomes and are useful epidemiological tools for planners and evaluators of health interventions. The
Passing in Command Line Arguments and Parallel Cluster/Multicore Batching in R with batch [0.03%]
R中的命令行参数传递和批量处理中的平行集群/多核批处理（英语）
Thomas J Hoffmann
Thomas J Hoffmann
It is often useful to rerun a command line R script with some slight change in the parameters used to run it - a new set of parameters for a simulation, a different dataset to process, etc. The R package batch provides a means to pass in mu...
Bayesian Semi- and Non-parametric Models for Longitudinal Data with Multiple Membership Effects in R [0.03%]
基于R的多重成员效应纵向数据的贝叶斯半参数和非参模型
Terrance D Savitsky,Susan M Paddock
Terrance D Savitsky
We introduce growcurves for R that performs analysis of repeated measures multiple membership (MM) data. This data structure arises in studies under which an intervention is delivered to each subject through the subject's participation in a...
POWERLIB: SAS/IML Software for Computing Power in Multivariate Linear Models [0.03%]
Powerlib：多元线性模型中SAS/IML软件的计算功效
Jacqueline L Johnson,Keith E Muller,James C Slaughter et al.
Jacqueline L Johnson et al.
The POWERLIBSAS/IML software provides convenient power calculations for a wide range of multivariate linear models with Gaussian errors. The software includes the Box, Geisser-Greenhouse, Huynh-Feldt, and uncorrected tests in the "univariat...