Predictions
ID
Lang
Model name
Repository
Description
Model 2 - Weekly and yearly (rw1) 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.
Temp-SPI Interaction Model
Validation test 1 for three-way interaction model (TO)
LSTM model for Infodengue Sprint
Predictions for 2024 in GO using the att_3 architecture
LSTM model for Infodengue Sprint
Predictions for 2023 in GO using the att_3 architecture
Prophet model with PCA and vaiance threshold
second test preds of the Prophet model in CE
Temp-SPI Interaction Model
Validation test 1 for three-way interaction model (RN)
Model 2 - Weekly and yearly (rw1) 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 follows a RW(1) process.
LSTM model for Infodengue Sprint
Predictions for 2023 in CE using the baseline_msle architecture
Temp-SPI Interaction Model
Validation test 2 for three-way interaction model (MT)
Temp-SPI Interaction Model
Validation test 2 for three-way interaction model (SE)
Temp-SPI Interaction Model
Validation test 2 for three-way interaction model (ES)
Temp-SPI Interaction Model
Validation test 2 for three-way interaction model (DF)
Random Forest model with uncertainty computed with conformal prediction
Forecast de novos casos para o geocode 2800308 entre 2022-01-01 e 2023-01-01 usando apenas os dados de 2800308 como input
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.
Temp-SPI Interaction Model
2024/25 forecast for three-way interaction model (SP)
Temp-SPI Interaction Model
2024/25 forecast for three-way interaction model (BA)
2025 sprint test - Sarima
2025 - Sarima - Preditores da picada
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.
LaCiD/UFRN
Dengue predictions for AL using Validation Test 1
Model 2 - Weekly and yearly (rw1) 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 follows a RW(1) process.
Temp-SPI Interaction Model
Validation test 1 for three-way interaction model (MT)
Temp-SPI Interaction Model
Validation test 1 for three-way interaction model (MG)
Temp-SPI Interaction Model
Validation test 2 for three-way interaction model (MA)
Temp-SPI Interaction Model
Validation test 2 for three-way interaction model (AP)
Temp-SPI Interaction Model
Validation test 1 for three-way interaction model (ES)
Temp-SPI Interaction Model
Validation test 1 for three-way interaction model (PA)
2569 predictions
https://api.mosqlimate.org/api/registry/predictions/?page=55&per_page=30&
Page 55 of 86
