Cook's Distance Measures for Varying Coefficient Models with Functional Responses [0.03%]
带有函数响应的可变系数模型的距离cook测量法
Qibing Gao,Mihye Ahn,Hongtu Zhu
Qibing Gao
The aim of this paper is to develop Cook's distance measures for assessing the influence of both atypical curves and observations under varying coefficient model for functional responses. Our Cook's distance measures include Cook's distance...
Discussion of the paper "Clustering Random Curves Under Spatial Interdependence with Application to Service Accessibility" by Jiang and Serban [0.03%]
江颖 and Serban论文《在空间相关性下的随机曲线聚类及其在可达服务中的应用》的讨论
Jiaping Wang,Haipeng Shen,Hongtu Zhu
Jiaping Wang
The Cluster Elastic Net for High-Dimensional Regression With Unknown Variable Grouping [0.03%]
未知变量分组的高维回归的聚类弹性网络
Daniela M Witten,Ali Shojaie,Fan Zhang
Daniela M Witten
In the high-dimensional regression setting, the elastic net produces a parsimonious model by shrinking all coefficients towards the origin. However, in certain settings, this behavior might not be desirable: if some features are highly corr...
Garritt L Page,David B Dunson
Garritt L Page
In studies where data are generated from multiple locations or sources it is common for there to exist observations that are quite unlike the majority. Motivated by the application of establishing a reference value in an inter-laboratory se...
Changwon Lim,Pranab K Sen,Shyamal D Peddada
Changwon Lim
Quantitative high throughput screening (qHTS) assays use cells or tissues to screen thousands of compounds in a short period of time. Data generated from qHTS assays are then evaluated using nonlinear regression models, such as the Hill mod...
Analysis of High-Dimensional Structure-Activity Screening Datasets Using the Optimal Bit String Tree [0.03%]
基于最优位串树的高维结构活性筛选数据的分析方法研究
Ke Zhang,Jacqueline M Hughes-Oliver,S Stanley Young
Ke Zhang
A new classification method called the Optimal Bit String Tree is proposed to identify quantitative structure-activity relationships (QSARs). The method introduces the concept of a chromosome to describe the presence/absence context of a co...
Likelihood Analysis of Multivariate Probit Models Using a Parameter Expanded MCEM Algorithm [0.03%]
采用参数展开的MCEM算法进行多变量probit模型的似然分析
Huiping Xu,Bruce A Craig
Huiping Xu
Multivariate binary data arise in a variety of settings. In this paper, we propose a practical and efficient computational framework for maximum likelihood estimation of multivariate probit regression models. This approach uses the Monte Ca...
Online Prediction Under Model Uncertainty via Dynamic Model Averaging: Application to a Cold Rolling Mill [0.03%]
模型不确定性下的在线预测及其在冷轧机中的应用
Adrian E Raftery,Miroslav Kárný,Pavel Ettler
Adrian E Raftery
We consider the problem of online prediction when it is uncertain what the best prediction model to use is. We develop a method called Dynamic Model Averaging (DMA) in which a state space model for the parameters of each model is combined w...
Partitioning degrees of freedom in hierarchical and other richly-parameterized models [0.03%]
层次模型及其他参数丰富的模型中自由度的分割方法
Yue Cui,James S Hodges,Xiaoxiao Kong et al.
Yue Cui et al.
Hodges & Sargent (2001) developed a measure of a hierarchical model's complexity, degrees of freedom (DF), that is consistent with definitions for scatterplot smoothers, interpretable in terms of simple models, and that enables control of a...
Simultaneous Determination of Tuning and Calibration Parameters for Computer Experiments [0.03%]
计算机实验的调节与标定参数的同时确定方法研究
Gang Han,Thomas J Santner,Jeremy J Rawlinson
Gang Han
Tuning and calibration are processes for improving the representativeness of a computer simulation code to a physical phenomenon. This article introduces a statistical methodology for simultaneously determining tuning and calibration parame...