Dynamic Prediction of Alternating Recurrent Events via Neural Network
Alternating recurrent events -- event-times of a specific nature that trigger a secondary refractory period -- occur in a wide-range of fields, including behavioral science, criminal justice, and biostatistics. Analysis of these events requires careful attention to the statistical nuance, including correlated observations and repeated outcomes subject to potential censoring. We develop an online dynamic prediction framework appropriate for predicting subsequent alternating recurrent events, by developing neural network theory for a statistical audiences and applying inverse probability weighted pseudo-observations. The proposed model is applied to dynamically predict alternating recurrent...
| Authors | Abigail Loe, Susan Murry, Zhenke Wu |
|---|---|
| Primary category | stat.ML |
| Published | 29 June 2026 |
| Last updated at source | 29 June 2026 |
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