J Kenneth Tay,Robert Tibshirani
J Kenneth Tay
Sparse generalised additive models (GAMs) are an extension of sparse generalised linear models that allow a model's prediction to vary non-linearly with an input variable. This enables the data analyst build more accurate models, especially...
On testing for homogeneity with zero-inflated models through the lens of model misspecification [0.03%]
基于模型规范错误的零膨胀模型的同质性检验
Wei-Wen Hsu,Nadeesha R Mawella,David Todem
Wei-Wen Hsu
In many applications of two-component mixture models such as the popular zero-inflated model for discrete-valued data, it is customary for the data analyst to evaluate the inherent heterogeneity in view of observed data. To this end, the sc...
Wesley Tansey,Yixin Wang,Raul Rabadan et al.
Wesley Tansey et al.
Analyzing data from large-scale, multi-experiment studies requires scientists to both analyze each experiment and to assess the results as a whole. In this article, we develop double empirical Bayes testing (DEBT), an empirical Bayes method...
Semiparametric Regression Analysis of Panel Count Data: A Practical Review [0.03%]
面板计数数据的半参数回归分析：实用综述
Sy Han Chiou,Chiung-Yu Huang,Gongjun Xu et al.
Sy Han Chiou et al.
Panel count data arise in many applications when the event history of a recurrent event process is only examined at a sequence of discrete time points. In spite of the recent methodological developments, the availability of their software i...
Geostatistical Methods for Disease Mapping and Visualisation Using Data from Spatio-temporally Referenced Prevalence Surveys [0.03%]
基于时空位置的患病率调查数据的疾病地图制图和可视化方法的地理统计学方法研究
Emanuele Giorgi,Peter J Diggle,Robert W Snow et al.
Emanuele Giorgi et al.
In this paper, we set out general principles and develop geostatistical methods for the analysis of data from spatio-temporally referenced prevalence surveys. Our objective is to provide a tutorial guide that can be used in order to identif...
Lu Tang,Yiwang Zhou,Lili Wang et al.
Lu Tang et al.
Multi-compartment models have been playing a central role in modelling infectious disease dynamics since the early 20th century. They are a class of mathematical models widely used for describing the mechanism of an evolving epidemic. Integ...
Mevin Hooten,Christopher Wikle,Michael Schwob
Mevin Hooten
A variety of demographic statistical models exist for studying population dynamics when individuals can be tracked over time. In cases where data are missing due to imperfect detection of individuals, the associated measurement error can be...
Alan H Dorfman
Alan H Dorfman
Statistical criteria are needed by which to evaluate the potential success or failure of applications of small area estimation. A necessary step to achieve this is a protocol-a series of steps-by which to assess whether an instance of small...
Review and Comparison of Computational Approaches for Joint Longitudinal and Time-to-Event Models [0.03%]
联合纵向和生存数据模型的计算方法及其比较综述
Allison K C Furgal,Ananda Sen,Jeremy M G Taylor
Allison K C Furgal
Joint models for longitudinal and time-to-event data are useful in situations where an association exists between a longitudinal marker and an event time. These models are typically complicated due to the presence of shared random effects a...
Eugene Demidenko
Eugene Demidenko
Many industrial and engineering applications are built on the basis of differential equations. In some cases, parameters of these equations are not known and are estimated from measurements leading to an inverse problem. Unlike many other p...