Model: ReichLab - SARIMA model without seasonal differencing API

    Name: SARIMA model without seasonal differencing
    Abbreviation: SARIMA1
    Owner: kgle
    Project: Khoa_test_project
    Team name: ReichLab
    Description: Team name: ReichLab.
    Team members: Evan L. Ray, Nicholas G. Reich.
    Data source(s): ilinet.
    Methods: A seasonal ARIMA model is fit using the auto.arima function in the forecast package for R. The data are log-transformed and any infinite or missing values after the transformation are linearly imputed before fitting the model. A separate model is fit for each region. Through iterating the one-step-ahead predictions, this model fit yields a joint predictive distribution for incidence in all remaining weeks of the season. Appropriate integrals of this joint distribution are calculated via Monte Carlo integration to obtain predictions for the seasonal quantities. For making prospective predictions for each season, only data before the start of that season were used in fitting model parameters. All code used in estimation and prediction is available at https://github.com/reichlab/2017-2018-cdc-flu-contest
    Home: https://github.com/FluSightNetwork/cdc-flusight-ensemble/tree/master/model-forecasts/component-models/ReichLab_sarima_seasonal_difference_FALSE
    Auxiliary data: (No auxiliary data)

    Forecasts (2)

    Timezero Data Source Upload Date
    2019-10-14 EW42-2019-ReichLab_sarima_seasonal_difference_FALSE_backfill_none.csv 2019-11-06 05:57:54
    2019-10-21 EW43-2019-ReichLab_sarima_seasonal_difference_FALSE_backfill_none.csv 2019-11-08 09:32:58