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pro vyhledávání: '"Bracher, Johannes"'
Divergence functions are measures of distance or dissimilarity between probability distributions that serve various purposes in statistics and applications. We propose decompositions of Wasserstein and Cram\'er distances$-$which compare two distribut
Externí odkaz:
http://arxiv.org/abs/2408.09770
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 armed conflicts, positive and negative log-changes in monthly fatalities r
Externí odkaz:
http://arxiv.org/abs/2304.12108
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 engage in practical forecasting, which requires a diverse set of skill
Externí odkaz:
http://arxiv.org/abs/2211.16171
Autor:
Bracher, Johannes, Sobolová, Barbora
INAR (integer-valued autoregressive) and INGARCH (integer-valued GARCH) models are among the most commonly employed approaches for count time series modelling, but have been studied in largely distinct strands of literature. In this paper, a new clas
Externí odkaz:
http://arxiv.org/abs/2204.12449
Autor:
Ray, Evan L., Brooks, Logan C., Bien, Jacob, Biggerstaff, Matthew, Bosse, Nikos I., Bracher, Johannes, Cramer, Estee Y., Funk, Sebastian, Gerding, Aaron, Johansson, Michael A., Rumack, Aaron, Wang, Yijin, Zorn, Martha, Tibshirani, Ryan J., Reich, Nicholas G.
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 ensemble that combines forecasts from these teams. These experiments have inf
Externí odkaz:
http://arxiv.org/abs/2201.12387
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 intervals at various levels. This is also the case for the forecasts collecte
Externí odkaz:
http://arxiv.org/abs/2005.12881
Autor:
Bracher, Johannes, Held, Leonhard
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 from the endemic-epidemic class to underreported data. The approach is
Externí odkaz:
http://arxiv.org/abs/2003.05885
Autor:
Bracher, Johannes
Publikováno v:
In: Steland, A., Rafajlowicz, E., Okhrin, O. (Eds.): Stochastic Models, Statistics and Their Applications, p. 323-333, Springer Nature Switzerland, 2019
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 a binomially thinned INAR(1) process. This allows us to obtain some o
Externí odkaz:
http://arxiv.org/abs/1910.07244
Autor:
Bracher, Johannes
In recent years the Centers for Disease Control and Prevention (CDC) have organized FluSight influenza forecasting competitions. To evaluate the participants' forecasts a multibin logarithmic score has been created, which is a non-standard variant of
Externí odkaz:
http://arxiv.org/abs/1910.07084
Autor:
Ray, Evan L., Brooks, Logan C., Bien, Jacob, Biggerstaff, Matthew, Bosse, Nikos I., Bracher, Johannes, Cramer, Estee Y., Funk, Sebastian, Gerding, Aaron, Johansson, Michael A., Rumack, Aaron, Wang, Yijin, Zorn, Martha, Tibshirani, Ryan J., Reich, Nicholas G.
Publikováno v:
In International Journal of Forecasting July-September 2023 39(3):1366-1383
