Time-varying coefficient cumulative gap time models for intensive longitudinal ecological momentary assessment data with missingness [0.03%]
具有缺失性的密集纵向生态瞬时评估数据的时变系数累积间隔时间模型
Xiaoxue Li,Stewart J Anderson,Saul Shiffman et al.
Xiaoxue Li et al.
Ecological momentary assessment (EMA) studies investigate intensive repeated observations of the current behavior and experiences of subjects in real time. In particular, such studies aim to minimize recall bias and maximize ecological vali...
Kostas Loumponias,George Tsaklidis
Kostas Loumponias
This paper concerns Kalman filtering when the measurements of the process are censored. The censored measurements are addressed by the Tobit model of Type I and are one-dimensional with two censoring limits, while the (hidden) state vectors...
Lingzhe Guo,Reza Modarres
Lingzhe Guo
Online change point detection methods monitor changes in the distribution of a data stream. This article discusses two non-parametric online change detection methods based on the energy statistics and Mahalanobis depth. To apply the energy ...
A surrogate model for estimating extreme tower loads on wind turbines based on random forest proximities [0.03%]
基于随机森林相似性的估计风力发电机组极端塔载荷的代理模型
Mikkel Slot Nielsen,Victor Rohde
Mikkel Slot Nielsen
In the present paper, we present a surrogate model, which can be used to estimate extreme tower loads on a wind turbine from a number of signals and a suitable simulation tool. Due to the requirements of the International Electrotechnical C...
Min Wang,Fang Chen,Tao Lu et al.
Min Wang et al.
In this paper, we develop Bayes factor based testing procedures for the presence of a correlation or a partial correlation. The proposed Bayesian tests are obtained by restricting the class of the alternative hypotheses to maximize the prob...
Quantifying conditional probability tables in Bayesian networks: Bayesian regression for scenario-based encoding of elicited expert assessments on feral pig habitat [0.03%]
基于场景的编码专家评估Bayesian回归量化贝叶斯网络中的条件概率表以野猪栖息地为案例分析
Ibrahim Alkhairy,Samantha Low-Choy,Justine Murray et al.
Ibrahim Alkhairy et al.
Bayesian networks are now widespread for modelling uncertain knowledge. They graph probabilistic relationships, which are quantified using conditional probability tables (CPTs). When empirical data are unavailable, experts may specify CPTs....
Robust signed-rank estimation and variable selection for semi-parametric additive partial linear models [0.03%]
半参数可加部分线性模型的稳健秩估计和变量选择方法研究
Brice M Nguelifack,Isabelle Kemajou-Brown
Brice M Nguelifack
A fully nonparametric model may not perform well or when the researcher wants to use a parametric model but the functional form with respect to a subset of the regressors or the density of the errors is not known. This becomes even more cha...
Clustering of longitudinal interval-valued data via mixture distribution under covariance separability [0.03%]
基于协方差可分性的区间值纵向数据混合分布聚类方法研究
Seongoh Park,Johan Lim,Hyejeong Choi et al.
Seongoh Park et al.
We consider the clustering of repeatedly measured 'min-max' type interval-valued data. We read the data as matrix variate data and assume the covariance matrix is separable for the model-based clustering (M-clustering). The use of a separab...
A class of residuals for outlier identification in zero adjusted regression models [0.03%]
零点调整回归模型中的异常值识别残差类方法
Gustavo H A Pereira,Juliana Scudilio,Manoel Santos-Neto et al.
Gustavo H A Pereira et al.
Zero adjusted regression models are used to fit variables that are discrete at zero and continuous at some interval of the positive real numbers. Diagnostic analysis in these models is usually performed using the randomized quantile residua...
Location-scale mixed models and goodness-of-fit assessment applied to insect ecology [0.03%]
位置尺度混合模型及拟合优度评估在昆虫生态学中的应用
R A Moral,J Hinde,E M M Ortega et al.
R A Moral et al.
Survival models have been extensively used to analyse time-until-event data. There is a range of extended models that incorporate different aspects, such as overdispersion/frailty, mixtures, and flexible response functions through semi-para...