6 papers
Monitoring a developing pandemic with available data
MarÃa Luz Gámiz, Enno Mammen, MarÃa Dolores MartÃnez-Miranda +3
This paper addresses statistical modelling and forecasting of key indicators describing the severity of a developing pandemic, using routinely reported daily counts of infections,…
Low quality exposure and point processes with a view to the first phase of a pandemic
MarÃa Luz Gámiz, Enno Mammen, MarÃa Dolores MartÃnez-Miranda +1
In the early days of a pandemic there is no time for complicated data collection. One needs a simple cross-country benchmark approach based on robust data that is easy to understan…
Local Limit Theorems and Strong Approximations for Robbins-Monro Procedures
Valentin Konakov, Enno Mammen, Lorick Huang
The Robbins-Monro algorithm is a recursive, simulation-based stochastic procedure to approximate the zeros of a function that can be written as an expectation. It is known that und…
Pure interaction effects unseen by Random Forests
Ricardo Blum, Munir Hiabu, Enno Mammen +1
Random Forests are widely claimed to capture interactions well. However, some simple examples suggest that they perform poorly in the presence of certain pure interactions that the…
Smooth Backfitting for Additive Hazard Rates
Stephan M. Bischofberger, Munir Hiabu, Enno Mammen +1
Smooth backfitting was first introduced in an additive regression setting via a direct projection alternative to the classic backfitting method by Buja, Hastie and Tibshirani. This…
Common Drivers in Sparsely Interacting Hawkes Processes
Alexander Kreiss, Enno Mammen, Wolfgang Polonik
We study a multivariate Hawkes process as a model for time-continuous relational event networks. The model does not assume the network to be known, it includes covariates, and it a…