323 citations · 351 across the 11 of their papers we have counts for
11 papers
Information leakage from data revisions in retrospective forecasts
Johannes Bracher, Sebastian Funk
Aygün et al (2026, https://doi.org/10.1038/s41586-026-10658-6) claim that their AI-driven Empirical Research Assistance (ERA) system produces COVID-19 hospitalisation forecasts whi…
Direction Augmentation in the Evaluation of Armed Conflict Predictions
Johannes Bracher, Lotta Rüter, Fabian Krüger +2
In many forecasting settings, there is a specific interest in predicting the sign of an outcome variable correctly in addition to its magnitude. For instance, when forecasting arme…
Learning to forecast: The probabilistic time series forecasting challenge
Johannes Bracher, Nils Koster, Fabian Krüger +1
We report on a course project in which students submit weekly probabilistic forecasts of two weather variables and one financial variable. This real-time format allows students to…
Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States
Evan L. Ray, Logan C. Brooks, Jacob Bien +12
The U.S. COVID-19 Forecast Hub aggregates forecasts of the short-term burden of COVID-19 in the United States from many contributing teams. We study methods for building an ensembl…
Evaluating epidemic forecasts in an interval format
Johannes Bracher, Evan L. Ray, Tilmann Gneiting +1
For practical reasons, many forecasts of case, hospitalization and death counts in the context of the current COVID-19 pandemic are issued in the form of central predictive interva…
A marginal moment matching approach for fitting endemic-epidemic models to underreported disease surveillance counts
Johannes Bracher, Leonhard Held
Count data are often subject to underreporting, especially in infectious disease surveillance. We propose an approximate maximum likelihood method to fit count time series models f…
A new INARMA(1, 1) model with Poisson marginals
Johannes Bracher
We suggest an INARMA(1, 1) model with Poisson marginals which extends the INAR(1) in a similar way as the INGARCH(1, 1) does for the INARCH(1) model. The new model is equivalent to…
An extended note on the multibin logarithmic score used in the FluSight competitions
Johannes Bracher
In recent years the Centers for Disease Control and Prevention (CDC) have organized FluSight influenza forecasting competitions. To evaluate the participants' forecasts a multibin…
Endemic-epidemic models with discrete-time serial interval distributions for infectious disease prediction
Johannes Bracher, Leonhard Held
Multivariate count time series models are an important tool for the analysis and prediction of infectious disease spread. We consider the endemic-epidemic framework, an autoregress…
Comment on "Under-reported data analysis with INAR-hidden Markov chains"
Johannes Bracher
In Fernandez-Fontelo et al (Statis. Med. 2016, DOI 10.1002/sim.7026) hidden integer-valued autoregressive (INAR) processes are used to estimate reporting probabilities for various…
Periodically stationary multivariate autoregressive models
Johannes Bracher, Leonhard Held
A class of multivariate periodic autoregressive models is proposed where coupling between time series is achieved through linear mean functions. Various response distributions with…