Subsampling focuses on selecting a subsample that can efficiently sketch the information of
the original data in terms of statistical inference. It provides a powerful tool in big data …

This paper presents a selective review of statistical computation methods for massive data
analysis. A huge amount of statistical methods for massive data computation have been …

Predictive analytics involves the use of statistical models to make predictions; however, the
power of these techniques is hindered by ever-increasing quantities of data. The richness …

This article introduces CluBear, a Python-based open-source package for interactive
massive data analysis. The key feature of CluBear is that it enables users to conduct …

Bagging is a useful method for large‐scale statistical analysis, especially when the
computing resources are very limited. We study here the asymptotic properties of bagging …

In this paper, we propose a novel approach for tackling the obstacles of empirical likelihood
in the face of massive data, which is called split sample mean empirical likelihood (SSMEL) …

La corrosión es un problema recurrente en la industria del gas natural, debido a la
presencia de gases corrosivos como el CO2 y el H2S que en presencia de agua pueden …

La corrosión es un problema recurrente en la industria del gas natural, debido a la
presencia de gases corrosivos como el CO 2 y el H 2 S que en presencia de agua pueden …

Para el desarrollo de la investigación se obtuvo una muestra de 46 cromatografías de gas
natural de bases de datos de Petróleos de Venezuela (PDVSA) de la región oriental de …