Model-based clustering provides a principled way of developing clustering methods. We develop a new model-based clustering methods for count data. The method combines clustering and variable selection ...

Objectives: To develop a diagnostic prediction model for rapidly progressive central precocious puberty (RP-CPP) and evaluate the contribution of osteocalcin(OC) to the model. Methods: For a total of ...

Abstract: This paper focuses on the design and application of a multivariate financial time series prediction model based on the Transformer, with the goal of enhancing forecast accuracy and ...

In this repository, we present the code of "CMamba: Channel Correlation Enhanced State Space Models for Multivariate Time Series Forecasting". conda create -n cmamba ...

Abstract: To address the challenges of traditional marine meteorological prediction methods, which struggle to effectively capture intervariable correlations in multivariate time series data and ...