Ayesha Talib,Sajid Ali,Ismail Shah
Ayesha Talib
Control charts are sophisticated graphical tools used to detect and control aberrant variations. Different control schemes are designed to continuously monitor and improve the process stability and performance. This study proposes a bivaria...
Interval-valued scalar-on-function linear quantile regression based on the bivariate center and radius method [0.03%]
基于双变量中心和半径法的区间值标量对函数线性分位数回归
Kaiyuan Liu,Min Xu,Jiang Du et al.
Kaiyuan Liu et al.
Interval-valued functional data, a new type of data in symbolic data analysis, depicts the characteristics of a variety of big data and has drawn the attention of many researchers. Mean regression is one of the important methods for analyzi...
Integrative analysis of high-dimensional quantile regression with contrasted penalization [0.03%]
具对比惩罚的高维分位数回归的集成分析
Panpan Ren,Xu Liu,Xiao Zhang et al.
Panpan Ren et al.
In the era of big data, the simultaneous analysis of multiple high-dimensional, heavy-tailed datasets has become essential. Integrative analysis offers a powerful approach to combine and synthesize information from these various datasets, a...
A robust and efficient change point detection method for high-dimensional linear models [0.03%]
高维线性模型的一种稳健高效的变化点检测方法
Zhong-Cheng Han,Kong-Sheng Zhang,Yan-Yong Zhao
Zhong-Cheng Han
In the context of linear models, a key problem of interest is to estimate the regression coefficient. Nevertheless, in certain instances, the vector of unknown coefficient parameters in a linear regression model differs from one segment to ...
Qunzhi Xu,Hongzhen Tian,Ananda Sarkar et al.
Qunzhi Xu et al.
This work studies rollout design problems with a focus of suitable choices of rollout rate under the standard Type I and Type II error probabilities control framework. The main challenge of rollout design is that data is often observed in a...
To impute or not? Testing multivariate normality on incomplete dataset: revisiting the BHEP test [0.03%]
要填充还是不要填充？在不完整数据集上测试多元正态性：再探BHEP检验
Danijel G Aleksić,Bojana Milošević
Danijel G Aleksić
In this paper, we focus on testing multivariate normality using the BHEP test with data that are missing completely at random. Our objective is twofold: first, to gain insight into the asymptotic behavior of the BHEP test statistics under t...
Sample Size Selection in Clinical Trials when Population Means Are Subject to a Partial Order: One-sided Ordered Alternatives [0.03%]
当总体均值存在部分序时在临床试验中选择样本量：单边有序备择假设
Bahadur Singh,Susan Halabi,Michael J Schell
Bahadur Singh
The statistical methodology under order restriction is very mathematical and complex. Thus, we provide a brief methodological background of order restricted likelihood ratio tests for the normal theory case for the basic understanding of it...
Dongyan Yan,Subharup Guha
Dongyan Yan
Rapid technological advances have allowed for molecular profiling across multiple omics domains for clinical decision-making in many diseases, especially cancer. However, as tumor development and progression are biological processes involvi...
A defective cure rate quantile regression model for male breast cancer data [0.03%]
一种用于男性乳腺癌数据的缺陷治愈率分位数回归模型
Agatha Rodrigues,Patrick Borges,Bruno Santos
Agatha Rodrigues
In this article, we particularly address the problem of assessing the impact of different prognostic factors, such as clinical stage and age, on the specific survival times of men with breast cancer when cure is a possibility. To this end, ...
Latent class profile model with time-dependent covariates: a study on symptom patterning of patients for head and neck cancer [0.03%]
具有时间依赖性协变量的潜在类别轮廓模型及其在头颈部癌症患者症状模式研究中的应用
Jung Wun Lee,Hayley Dunnack Yackel
Jung Wun Lee
The latent class profile model (LCPM) is a widely used technique for identifying distinct subgroups within a sample based on observations' longitudinal responses to categorical items. This paper proposes an expanded version of LCPM by embed...