Peter C Austin
Peter C Austin
In time-to-event analyses, a competing risk is an event whose occurrence precludes the occurrence of the event of interest. Settings with competing risks occur frequently in clinical research. Missing data, which is a common problem in rese...
An Extended Langevinized Ensemble Kalman Filter for non-Gaussian Dynamic Systems [0.03%]
一种扩展的朗之万化集合卡尔曼滤波方法及其在非高斯动态系统中的应用
Peiyi Zhang,Tianning Dong,Faming Liang
Peiyi Zhang
State estimation for large-scale non-Gaussian dynamic systems remains an unresolved issue, given nonscalability of the existing particle filter algorithms. To address this issue, this paper extends the Langevinized ensemble Kalman filter (L...
A New Approach to Modeling the Cure Rate in the Presence of Interval Censored Data [0.03%]
间断检测数据下建模治愈率的新方法
Suvra Pal,Yingwei Peng,Wisdom Aselisewine
Suvra Pal
We consider interval censored data with a cured subgroup that arises from longitudinal followup studies with a heterogeneous population where a certain proportion of subjects is not susceptible to the event of interest. We propose a two com...
Chung Chang,R Todd Ogden,Yakuan Chen
Chung Chang
In recent years, several methods have been proposed to deal with functional data classification problems (e.g., one-dimensional curves or two- or three-dimensional images). One popular general approach is based on the kernel-based method, p...
Joint Bayesian longitudinal models for mixed outcome types and associated model selection techniques [0.03%]
混合结果类型的联合贝叶斯纵向模型及其相关的模型选择技术
Nicholas Seedorff,Grant Brown,Breanna Scorza et al.
Nicholas Seedorff et al.
Motivated by data measuring progression of leishmaniosis in a cohort of US dogs, we develop a Bayesian longitudinal model with autoregressive errors to jointly analyze ordinal and continuous outcomes. Multivariate methods can borrow strengt...
Armando Tapia,Silvestre L González,Jose R Vergara et al.
Armando Tapia et al.
The interest of this article is to better understand the effects of different public policy alternatives to handle the COVID-19 pandemic. In this work we use the susceptible, infected, recovered (SIR) model to find which of these policies h...
Spatio-temporal clustering analysis using generalized lasso with an application to reveal the spread of Covid-19 cases in Japan [0.03%]
基于广义LASSO的时空聚类分析及其在日本COVID-19传播中的应用
Septian Rahardiantoro,Wataru Sakamoto
Septian Rahardiantoro
This study addressed the issue of determining multiple potential clusters with regularization approaches for the purpose of spatio-temporal clustering. The generalized lasso framework has flexibility to incorporate adjacencies between objec...
Pseudo-document simulation for comparing LDA, GSDMM and GPM topic models on short and sparse text using Twitter data [0.03%]
基于Twitter数据的LDA、GSDMM和GPM主题模型在短文本和稀疏文本上对比研究伪文档模拟
Christoph Weisser,Christoph Gerloff,Anton Thielmann et al.
Christoph Weisser et al.
Topic models are a useful and popular method to find latent topics of documents. However, the short and sparse texts in social media micro-blogs such as Twitter are challenging for the most commonly used Latent Dirichlet Allocation (LDA) to...
Carlos Rondero-Guerrero,Isidro González-Hernández,Carlos Soto-Campos
Carlos Rondero-Guerrero
A new uniform distribution model, generalized powered uniform distribution (GPUD), which is based on incorporating the parameter k into the probability density function (pdf) associated with the power of random variable values and includes ...
Roy Cerqueti,Raffaele Mattera,Germana Scepi
Roy Cerqueti
This paper proposes a clustering approach for multivariate time series with time-varying parameters in a multiway framework. Although clustering techniques based on time series distribution characteristics have been extensively studied, met...