In high-dimensional data analysis, we propose a sequential model averaging (SMA) method to make accurate and stable predictions. Specifically, we introduce a hybrid approach that combines a sequential ...

By implementing dimensional modeling, businesses can report, query, and analyze data. Facts, dimensions, and attributes make up the core of dimensional modeling. Facts are categorised as additive, ...

Technical Background and Innovation The emergence of the 'Lingji Smart City' large model relies on nearly a century of accumulated engineering drawing data from the Chongqing Design Institute, ...

This paper shows that the Expectation-Maximization (EM) algorithm for regime-switching dynamic factor models provides satisfactory performance relative to other estimation methods and delivers a good ...

A dimensional model is a type of data model that is less rigid and structured than other types of models. It is best for a contextual data structure that is more related to the business use or ...

Data with high-dimensional covariates are now commonly encountered. Compared to other types of responses, research on high-dimensional data with censored survival responses is still relatively limited ...

Conclusively, Multi-Dimensional Modeling plays a crucial role in empowering decision-making and driving process improvements in enterprise data management. By providing a comprehensive view of data ...

At the launch event of the 'Lingji Smart City' large model product held in Chongqing, a groundbreaking urban digital twin technology was officially unveiled. This product was developed by the ...