A comprehensive estimator for the Fréchet distribution: asymptotical efficiency, and practical applications to health studies [0.03%]
一个完整的Fréchet分布估计器的构建及其在健康研究中的应用
Sang Kyu Lee,Hyokyoung G Hong,Hyoung-Moon Kim
Sang Kyu Lee
The Fréchet distribution is a fundamental tool in extreme value theory, with applications spanning various fields such as life testing, modeling extreme health-related events (such as infant birth weight extremes or rare disease outbreaks)...
Sangyeol Lee,Dongwon Kim
Sangyeol Lee
In this study, we consider an online monitoring procedure to detect a parameter change for bivariate time series of counts, following bivariate integer-valued generalized autoregressive heteroscedastic (BIGARCH) and autoregressive (BINAR) m...
A novel high-order multivariate Markov model for spatiotemporal analysis with application to COVID-19 outbreak [0.03%]
一种新的高阶多变量马尔可夫模型用于时空分析并在COVID-19疫情中应用
A M Elshehawey,Zhengming Qian
A M Elshehawey
We propose a new strategy for analyzing the evolution of random phenomena over time and space simultaneously based on the high-order multivariate Markov chains. We develop a novel Markov model of order r for m chains consisting of s possibl...
E P Sreedevi,Sudheesh K Kattumannil
E P Sreedevi
We develop new goodness of fit test for uniform distribution based on a conditional moment characterization. We study the asymptotic properties of the proposed test statistic. We also present a goodness of fit test for uniform distribution ...
Yinghua Li,Yongsong Qin
Yinghua Li
Spatial dynamic panel data (SDPD) models have received great attention in economics in recent 10 years. Existing approaches for the estimation and test of SDPD models are quasi-maximum likelihood (QML) approach and generalized method of mom...
Rejoinder: A comparison of Monte Carlo methods for computing marginal likelihoods of item response theory models [0.03%]
贝叶斯估计中用于计算项目反应理论模型边际似然的蒙特卡罗方法比较及讨论
Yang Liu,Guanyu Hu,Lei Cao et al.
Yang Liu et al.
Kwangmin Lee,Seongil Jo,Jaeyong Lee
Kwangmin Lee
In 2020, Korea Disease Control and Prevention Agency reported three rounds of surveys on seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in South Korea. SARS-CoV-2 is the virus which inflicts the co...
Inflated Density Ratio and Its Variation and Generalization for Computing Marginal Likelihoods [0.03%]
膨胀密度比及其变化和广义化在计算边缘似然中的应用
Yu-Bo Wang,Ming-Hui Chen,Wei Shi et al.
Yu-Bo Wang et al.
In the Bayesian framework, the marginal likelihood plays an important role in variable selection and model comparison. The marginal likelihood is the marginal density of the data after integrating out the parameters over the parameter space...
Detecting possibly frequent change-points: Wild Binary Segmentation 2 and steepest-drop model selection-rejoinder [0.03%]
可能频繁变化点的检测：Wild二进制分割法2和最大降幅模型选择--回应
Piotr Fryzlewicz
Piotr Fryzlewicz
Many existing procedures for detecting multiple change-points in data sequences fail in frequent-change-point scenarios. This article proposes a new change-point detection methodology designed to work well in both infrequent and frequent ch...
A Comparison of Monte Carlo Methods for Computing Marginal Likelihoods of Item Response Theory Models [0.03%]
若干求解项目反应理论模型边际似然的蒙特卡罗方法比较研究
Yang Liu,Guanyu Hu,Lei Cao et al.
Yang Liu et al.
Nowadays, Bayesian methods are routinely used for estimating parameters of item response theory (IRT) models. However, the marginal likelihoods are still rarely used for comparing IRT models due to their complexity and a relatively high dim...