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 ...
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 ...
Gender-disaggregated multivariate probit models were constructed to estimate the relationship between DHL and awareness of and access to sexual health products and services (eg, sexual and ...
Abstract: Multivariate time series classification tasks play a crucial role in the field of data mining and find wide applications in areas such as audio, healthcare, and transportation. The core ...
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