Forecasting hourly foodservice sales during geopolitical and economical disruption using zero-inflated mixed effects models [0.03%]
基于零膨胀混合效应模型的地理政治和经济动荡时期的餐饮销售小时预测
Nathan A Judd,Kalliopi Mylona,Haiming Liu et al.
Nathan A Judd et al.
Accurate predictions of product sales are essential to the foodservice sector, for planning and saving of resources. In this paper, a zero-inflated negative binomial mixed-effects model with several factors was used to predict the total sal...
Tuğba Aktaş Aslan,Başak Bulut Karageyik
Tuğba Aktaş Aslan
Effective risk management in actuarial science requires precise modeling of claim severity, particularly for heavy-tailed distributions that capture extreme losses. This study investigates the applicability of the Tempered Stable Subordinat...
Semiparametric analysis of competing risks data with missing causes of failure and covariate measurement error [0.03%]
具有缺失的失败原因和协变量测量误差的竞争风险数据的半参数分析
Akurathi Jayanagasri,S Anjana
Akurathi Jayanagasri
Competing risks data with missing causes of failure are common in biomedical studies. Often, competing risks data may arise with the covariates that are measured with error. In this work, we consider a semiparametric linear transformation m...
Optimizing personalized screening intervals for clinical biomarkers using extended joint models [0.03%]
利用扩展联合模型优化临床生物标志物的个性化筛查间隔
Nobuhle Nokubonga Mchunu,Henry Mwambi,Tarylee Reddy et al.
Nobuhle Nokubonga Mchunu et al.
This research advances joint modeling and personalized scheduling for HIV and TB by incorporating censored longitudinal outcomes in multivariate joint models, providing a more flexible and accurate approach for complex data scenarios. Inspi...
Estimating wildfire ignition probabilities with geographic weighted logistic regression [0.03%]
基于地理加权逻辑回归的火灾发生概率估计模型研究
Marco Marto,Sarah Santos,António Vieira et al.
Marco Marto et al.
Ignition probabilities play an important role in wildfire-related decision-making and can be included in quantitative approaches for risk management, fuel management and in prepositioning of firefighting resources. We are studying an area a...
A joint latent-class Bayesian model with application to ALL maintenance studies [0.03%]
一种联合潜在类别贝叶斯模型及其在ALL维持治疗研究中的应用
Damitri Kundu,Sevantee Basu,Manash Pratim Gogoi et al.
Damitri Kundu et al.
Acute Lymphocytic Leukemia (ALL) is globally the main cause of death from blood cancer among children. While the survival rate of ALL has increased significantly in the first-world countries (e.g. in the United States) over the last 50 year...
Robust Bayesian model averaging for linear regression models with heavy-tailed errors [0.03%]
具有厚尾误差的线性回归模型的稳健型贝叶斯模型平均方法
Shamriddha De,Joyee Ghosh
Shamriddha De
Our goal is to develop a Bayesian model averaging technique in linear regression models that accommodates heavier tailed error densities than the normal distribution. Motivated by the use of the Huber loss function in the presence of outlie...
Hassan Pazira,Emanuele Massa,Jetty A M Weijers et al.
Hassan Pazira et al.
To accurately estimate the parameters in a prediction model for survival data, sufficient events need to be observed compared to the number of model parameters. In practice, this is often a problem. Merging data sets from different medical ...
Multiple outlier detection in samples with exponential & Pareto tails [0.03%]
指数分布及pareto尾部样本组多重异常值的检验
Didier Sornette,Ran Wei
Didier Sornette
We introduce two ratio-based robust test statistics, max-robust-sum (MRS) and sum-robust-sum (SRS), which compare the largest suspected outlier(s) to a trimmed partial sum of the sample. They are designed to enhance the robustness of outlie...
Optimal distributed subsampling for accelerated failure time models with massive censored data [0.03%]
巨量删失数据下加速失效时间模型的最优分布式抽样方法
Chunjie Wang,Jing Li,Xiaohui Yuan
Chunjie Wang
The availability of massive data stored across multiple locations is increasing in many fields. The data at each site often exhibits large-scale features. Current research primarily focuses on such datasets that consist of uncensored observ...