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Mara Meggiorin, Giulia Passadore, Silvia Bertoldo, Andrea Sottani and Andrea Rinaldo
This study compares three imputation methods applied to the field observations of hydraulic head in subsurface hydrology. Hydrogeological studies that analyze the timeseries of groundwater elevations often face issues with missing data that may mislead b...
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Andrés F. Ochoa-Muñoz and Javier E. Contreras-Reyes
Missing or unavailable data (NA) in multivariate data analysis is often treated with imputation methods and, in some cases, records containing NA are eliminated, leading to the loss of information. This paper addresses the problem of NA in multiple facto...
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Saul G. Ramirez, Gustavious Paul Williams, Norman L. Jones, Daniel P. Ames and Jani Radebaugh
Obtaining and managing groundwater data is difficult as it is common for time series datasets representing groundwater levels at wells to have large gaps of missing data. To address this issue, many methods have been developed to infill or impute the mis...
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Xinxi Lu, Lijuan Yuan, Ruifeng Li, Zhihuan Xing, Ning Yao and Yichun Yu
In recent years, the development of computer technology has promoted the informatization and intelligentization of hospital management systems and thus produced a large amount of medical data. These medical data are valuable resources for research. We ca...
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Tiantian Liu and Yuanyuan Li
Single-cell RNA sequencing (scRNA-seq) has become a powerful technique to investigate cellular heterogeneity and complexity in various fields by revealing the gene expression status of individual cells. Despite the undeniable benefits of scRNA-seq, it is...
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