3 citations · 3 across the 1 of their papers we have counts for
4 papers
Asymptotic considerations in a Bayesian linear model with nonparametrically modelled time series innovations
Claudia Kirch, Alexander Meier, Renate Meyer +1
This paper considers a semiparametric approach within the general Bayesian linear model where the innovations consist of a stationary, mean zero Gaussian time series. While a param…
Scan statistics for the detection of anomalies in M-dependent random fields with applications to image data
Claudia Kirch, Philipp Klein, Marco Meyer
Anomaly detection in random fields is an important problem in many applications including the detection of cancerous cells in medicine, obstacles in autonomous driving and cracks i…
Bayesian nonparametric spectral analysis of locally stationary processes
Yifu Tang, Claudia Kirch, Jeong Eun Lee +1
Based on a novel dynamic Whittle likelihood approximation for locally stationary processes, a Bayesian nonparametric approach to estimating the time-varying spectral density is pro…
Beyond Whittle: Nonparametric correction of a parametric likelihood with a focus on Bayesian time series analysis
Claudia Kirch, Matthew C. Edwards, Alexander Meier +1
The Whittle likelihood is widely used for Bayesian nonparametric estimation of the spectral density of stationary time series. However, the loss of efficiency for non-Gaussian time…