Daniel Andrés Díaz-Pachón,Juan Pablo Sáenz,J Sunil Rao et al.
Daniel Andrés Díaz-Pachón et al.
We propose a new method to find modes based on active information. We develop an algorithm called active information mode hunting (AIMH) that, when applied to the whole space, will say whether there are any modes present and where they are....
Integrative Interaction Analysis using Threshold Gradient Directed Regularization [0.03%]
使用阈值梯度导向正则化的整合交互分析
Yang Li,Rong Li,Yichen Qin et al.
Yang Li et al.
For many complex business and industry problems, high-dimensional data collection and modeling have been conducted. It has been shown that interactions may have important implications beyond main effects. The number of unknown parameters in...
A Rappold,W G Müller,D C Woods
A Rappold
Blocking is often used to reduce known variability in designed experiments by collecting together homogeneous experimental units. A common modeling assumption for such experiments is that responses from units within a block are dependent. A...
Weak signals in high-dimension regression: detection, estimation and prediction [0.03%]
高维回归中的弱信号：检测、估计与预测
Yanming Li,Hyokyoung G Hong,S Ejaz Ahmed et al.
Yanming Li et al.
Regularization methods, including Lasso, group Lasso and SCAD, typically focus on selecting variables with strong effects while ignoring weak signals. This may result in biased prediction, especially when weak signals outnumber strong signa...
Wesley Lee,Bailey K Fosdick,Tyler H McCormick
Wesley Lee
Relational event data, which consist of events involving pairs of actors over time, are now commonly available at the finest of temporal resolutions. Existing continuous-time methods for modeling such data are based on point processes and d...
Peter Müller,Yanxun Xu,Peter F Thall
Peter Müller
The intent of this discussion is to highlight opportunities and limitations of utility-based and decision theoretic arguments in clinical trial design. The discussion is based on a specific case study, but the arguments and principles remai...
Maximum likelihood estimation for stochastic volatility in mean models with heavy-tailed distributions [0.03%]
带厚尾分布的 stochastic volatility in mean 模型的最大似然估计方法研究
Carlos A Abanto-Valle,Roland Langrock,Ming-Hui Chen et al.
Carlos A Abanto-Valle et al.
In this article, we introduce a likelihood-based estimation method for the stochastic volatility in mean (SVM) model with scale mixtures of normal (SMN) distributions (Abanto-Valle et al., 2012). Our estimation method is based on the fact t...
Werner G Müller,Luc Pronzato,Joao Rendas et al.
Werner G Müller et al.
For estimation and predictions of random fields, it is increasingly acknowledged that the kriging variance may be a poor representative of true uncertainty. Experimental designs based on more elaborate criteria that are appropriate for empi...