Predictions
ID
Lang
Model name
Repository
Description
318
Temp-SPI Interaction Model
2024/25 forecast for three-way interaction model (RN)
150
Temp-SPI Interaction Model
Validation test 2 for three-way interaction model (RS)
151
Temp-SPI Interaction Model
Validation test 2 for three-way interaction model (SC)
313
Temp-SPI Interaction Model
2024/25 forecast for three-way interaction model (AM)
363
Model 2 - Weekly and yearly (rw1) components
This upload represents the epidemic prediction for unseen data from the period of 2024-06-16 to 2025-10-05 in the state GO.
338
LSTM model for Infodengue Sprint
Predictions for 2025 in RS using the baseline architecture
341
LSTM model for Infodengue Sprint
Predictions for 2025 in SP using the baseline architecture
340
LSTM model for Infodengue Sprint
Predictions for 2025 in PR using the baseline architecture
314
Temp-SPI Interaction Model
2024/25 forecast for three-way interaction model (AL)
361
Model 2 - Weekly and yearly (rw1) components
This upload represents the epidemic prediction for unseen data from the period of 2024-06-16 to 2025-10-05 in the state AM.
484
LSTM model for Infodengue Sprint
Predictions for 2024 in SP using the baseline architecture
362
Model 2 - Weekly and yearly (rw1) components
This upload represents the epidemic prediction for unseen data from the period of 2024-06-16 to 2025-10-05 in the state CE.
342
LSTM model for Infodengue Sprint
Predictions for 2025 in MG using the baseline architecture
339
LSTM model for Infodengue Sprint
Predictions for 2025 in SC using the baseline architecture
138
Temp-SPI Interaction Model
Validation test 2 for three-way interaction model (MG)
315
Temp-SPI Interaction Model
2024/25 forecast for three-way interaction model (GO)
316
Temp-SPI Interaction Model
2024/25 forecast for three-way interaction model (PE)
311
Temp-SPI Interaction Model
2024/25 forecast for three-way interaction model (RJ)
358
Model 1 - Weekly and yearly (iid) components
This upload represents the epidemic prediction for unseen data from the period of 2024-06-16 to 2025-10-05 in the state GO. The model is founded on a structural decomposition designed for modeling counting series, employing a Poisson distribution. The log intensity is defined by the sum of weekly and yearly components, where the first one is defined as a AR(1) process and the last one is assumed to be iid.
195
Model 1 - Weekly and yearly (iid) components
The model is founded on a structural decomposition designed for modeling counting series, employing a Poisson distribution. The log intensity is defined by the sum of weekly and yearly components, where the first one is defined as a AR(1) process and the last one is assumed to be iid.
337
LSTM model for Infodengue Sprint
Predictions for 2025 in RN using the baseline architecture
336
LSTM model for Infodengue Sprint
Predictions for 2025 in SE using the baseline architecture
310
Temp-SPI Interaction Model
2024/25 forecast for three-way interaction model (MS)
334
LSTM model for Infodengue Sprint
Predictions for 2025 in PE using the baseline architecture
308
Temp-SPI Interaction Model
2024/25 forecast for three-way interaction model (MT)
703 predictions
https://api.mosqlimate.org/api/registry/predictions/?page=6&per_page=30&
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