Integer-valued max-autoregressive models The talk addresses an introduction to integer-valued max-autoregressive models. The parameter estimation for such models, e.g., the max-INAR(1) model, seems to be straightforward. The max-INAR(1) model is a Markov chain and maximum likelihood estimation with numerical optimization routines seems to be easily applicable. But if the observed counts attain very large values, […]
Changepoint detection in a nonparametric time series regression model A weakly dependent time series is considered, for which we develop a strategy to detect whether the nonparametric conditional mean function is stable in time. The strategy allows for autoregressive effects and heteroscedasticity. Our proposal is based on a modified CUSUM-type test procedure, which uses a […]
Effect Selection in Cox Frailty Models by Regularization Methods In all sorts of regression problems it has become more and more important to deal with complex and high dimensional data with lots of potentially influential covariates. A possible solution is to apply estimation methods that aim at the detection of the relevant effect structure by […]
Point Forecasting in Discrete Time Series Analysis In this work we determine central and non-central coherent point forecasts of various discrete valued time series models. Each coherent integer forecast is compared to its approximation, derived from the model representing the continuous counterpart to each respective discrete model. Several INAR(1) processes and the influence of their […]
Challenging the commonly used log-link in statistical models for count data with an application to infectious disease data A response function is an essential part of any generalized linear model, but its choice is rarely questioned. In particular, if the modeled expected value is restricted to be greater than zero, the choice often falls on […]
Adaptive Control charts for identifying concept drift in nonstationary environment Time adjusting dynamic systems whose underlying changing distribution should be continuously monitored to track abnormal behaviors is one of the most recent challenges in many real life applications. In fields such as sensor networks, intrusion detection, credit card fraud detection and process monitoring, the arriving […]
Health Care Monitoring by Hypergeometric Control Charts for Fractions Non-Conforming Process monitoring in health care organisations is one of the core tasks of an efficient medical risk management system for detecting, assessing, mitigating, and preventing risks. Statistical control charts as adequate tools for process monitoring are well-suited to observe, measure, and improve health care outcomes […]
Auf der Suche nach relevanten Merkmalen Die Selektion relevanter Merkmale ist ein zentrales Problem der Statistik und der empirischen Wissenschaften im Allgemeinen. Zwar lassen sich heute problemlos große Datenmengen erheben, also viele Merkmale zahlreicher statistischer Merkmalsträger festhalten, doch welche davon sind wichtig? Wie ist das kausale Gefüge und welche Variablen steuern das Geschehen? Schon im […]
Forecasting the Equity Premium: Mind the News! This paper introduces a novel strategy for predicting the monthly equity premium based on extracted news from more than 700,000 newspaper articles, published in The New York Times and Washington Post between 1980 and 2018. We propose a flexible data-adaptive switching approach to map a large set of […]
Some extensions to the endemic-epidemic model class for infectious disease surveillance counts The endemic-epidemic class (Held et al 2005, DOI 10.1191=1471082X05st098oa) is a modelling framework for multivariate infectious disease surveillance counts closely related to INGARCH models. It allows to model counts stratified by e.g. disease type, geographical area or age group and is readily implemented […]