A comparison of zero-inflated and hurdle models for modeling zero-inflated count data [0.03%]
零膨胀和障碍模型在零膨胀计数数据建模中的比较研究
Cindy Xin Feng
Cindy Xin Feng
Counts data with excessive zeros are frequently encountered in practice. For example, the number of health services visits often includes many zeros representing the patients with no utilization during a follow-up time. A common feature of ...
Mei Ling Huang,Christine Nguyen
Mei Ling Huang
For extreme events, estimation of high conditional quantiles for heavy tailed distributions is an important problem. Quantile regression is a useful method in this field with many applications. Quantile regression uses an L 1-loss function,...
Jean-François Plante
Jean-François Plante
Rank correlation is invariant to bijective marginal transformations, but it is not immune to confounding. Assuming a categorical confounding variable is observed, the author proposes weighted coefficients of correlation for continuous varia...
Goodness of fit for the logistic regression model using relative belief [0.03%]
相对信念下的逻辑回归模型的吻合度检验方法研究
Luai Al-Labadi,Zeynep Baskurt,Michael Evans
Luai Al-Labadi
A logistic regression model is a specialized model for product-binomial data. When a proper, noninformative prior is placed on the unrestricted model for the product-binomial model, the hypothesis H 0 of a logistic regression model holding ...
Mei Ling Huang,Christine Nguyen
Mei Ling Huang
Quantile regression estimates conditional quantiles and has wide applications in the real world. Estimating high conditional quantiles is an important problem. The regular quantile regression (QR) method often designs a linear or non-linear...
Parameters of stochastic models for electroencephalogram data as biomarkers for child's neurodevelopment after cerebral malaria [0.03%]
随机模型的参数作为儿童脑疟疾后的神经发育生物标志物：来自脑电图数据的研究
Maria A Veretennikova,Alla Sikorskii,Michael J Boivin
Maria A Veretennikova
The objective of this study was to test statistical features from the electroencephalogram (EEG) recordings as predictors of neurodevelopment and cognition of Ugandan children after coma due to cerebral malaria. The increments of the freque...
Marginalized mixture models for count data from multiple source populations [0.03%]
来源于多个源种群的计数数据的边缘化混合模型
Habtamu K Benecha,Brian Neelon,Kimon Divaris et al.
Habtamu K Benecha et al.
Mixture distributions provide flexibility in modeling data collected from populations having unexplained heterogeneity. While interpretations of regression parameters from traditional finite mixture models are specific to unobserved subpopu...
Missing data approaches for probability regression models with missing outcomes with applications [0.03%]
具有缺失结果的概率回归模型的缺失数据方法及其应用
Li Qi,Yanqing Sun
Li Qi
In this paper, we investigate several well known approaches for missing data and their relationships for the parametric probability regression model Pβ (Y|X) when outcome of interest Y is subject to missingness. We explore the relationship...
Failure time regression with continuous informative auxiliary covariates [0.03%]
具有连续性辅助协变量的失效时间回归分析
Lipika Ghosh,Jiancheng Jiang,Yanqing Sun et al.
Lipika Ghosh et al.
In this paper we use Cox's regression model to fit failure time data with continuous informative auxiliary variables in the presence of a validation subsample. We first estimate the induced relative risk function by kernel smoothing based o...