TFM: An R package for truncated factor model
The Truncated Factor Model (TFM) is a statistical model for analyzing high-dimensional truncated data, leveraging sparsity and online learning to extract common factors. Its core advantage is efficient modeling of complex data structures with flexible parameter adjustments. We developed an R package...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | SoftwareX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352711025001712 |
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| Summary: | The Truncated Factor Model (TFM) is a statistical model for analyzing high-dimensional truncated data, leveraging sparsity and online learning to extract common factors. Its core advantage is efficient modeling of complex data structures with flexible parameter adjustments. We developed an R package named TFM, which integrates methods like SOPC, SPC, PPC, SAPC, IPC, and ttest to compute factor loading and specific variance matrices. These methods were comprehensively evaluated using metrics such as estimation accuracy and mean squared error, demonstrating their effectiveness in handling truncated data. |
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| ISSN: | 2352-7110 |