Order selection in GARMA models for count time series: a Bayesian perspective [0.03%]
计数时间序列的GARMA模型订单选择：贝叶斯视角
Katerine Zuniga Lastra,Guilherme Pumi,Taiane Schaedler Prass
Katerine Zuniga Lastra
Estimation in GARMA models has traditionally been carried out under the frequentist approach. To date, Bayesian approaches for such estimation have been relatively limited. In the context of GARMA models for count time series, Bayesian esti...
Learning causal effect of physical activity distribution: an application of functional treatment effect estimation with unmeasured confounding [0.03%]
体力活动分布因果效应的学习：具未测量混杂因素的功能性处理效果估计的应用
Zhuoxin Long,Xiaoke Zhang
Zhuoxin Long
The National Health and Nutrition Examination Survey (NHANES) collects minute-level physical activity data by accelerometers as an important component of the survey to assess the health and nutritional status of adults and children in the U...
Zero-inflated Poisson mixed model for longitudinal count data with informative dropouts [0.03%]
具有信息丢失的纵向计数数据的零膨胀泊松混合模型
Sanjoy K Sinha
Sanjoy K Sinha
Zero-inflated Poisson (ZIP) models are typically used for analyzing count data with excess zeros. If the data are collected longitudinally, then repeated observations from a given subject are correlated by nature. The ZIP mixed model may be...
Calibrating a simulated exposure distribution using measurement error models [0.03%]
利用测量误差模型校准模拟暴露分布
Jiwoong Yu,Xueyan Zheng,Kwan-Young Bak et al.
Jiwoong Yu et al.
Indirect exposure assessment based on average environmental concentrations in microenvironments and time spent in each environment has been considered an important way of assessing personal exposure to air pollutants. Using this indirect ap...
V Gómez-Rubio,J Lagos,F Palmí-Perales
V Gómez-Rubio
Finding players with similar profiles is an important problem in sports such as football (also known as soccer in some countries). Scouting for new players requires a wealth of information about the available players so that similar profile...
New insights into multicollinearity in the Cox proportional hazard models: the Kibria-Lukman estimator and its application [0.03%]
Cox比例风险模型中多重共线性新见解：Kibria-Lukman估计量及其应用
Solmaz Seifollahi,Zakariya Yahya Algamal,Mohammad Arashi
Solmaz Seifollahi
This paper examines the Cox proportional hazards model (CPHM) in the presence of multicollinearity. Typically, the maximum partial likelihood estimator (MPLE) is employed to estimate the model coefficients, which works well when the covaria...
Amanda M Y Chu,Yasuhiro Omori,Hing-Yu So et al.
Amanda M Y Chu et al.
It is not uncommon for surveys in the social sciences to ask sensitive questions. Asking sensitive questions indirectly enables collecting of the desirable sensitive information while at the same time protecting respondents' data privacy. T...
Robust parameter estimation and variable selection in regression models for asymmetric heteroscedastic data [0.03%]
回归模型中用于非对称异方差数据的稳健参数估计和变量选择方法研究
Y Güney,O Arslan
Y Güney
In many real-world scenarios, not only the location but also the scale and even the skewness of the response variable may be influenced by explanatory variables. To achieve accurate predictions in such cases, it is essential to model locati...
Yang Li,Qijing Yan,Mixia Wu et al.
Yang Li et al.
Variance changepoints in economics, finance, biomedicine, oceanography, etc. are frequent and significant. To better detect these changepoints, we propose a new technique for constructing confidence intervals for the variances of a noisy se...
Amy M J O&#x;Shea,Jeffrey D Dawson
Amy M J O&#x;Shea
Time series data are increasingly common in many areas of the health sciences, and in some instances, may have natural boundaries serving as performance guidelines or as thresholds associated with adverse outcomes. Such boundaries may be la...