104 citations · 247 across the 19 of their papers we have counts for
10 papers · 1 filter
A nonparametrically corrected likelihood for Bayesian spectral analysis of multivariate time series
Yixuan Liu, Claudia Kirch, Jeong Eun Lee +1
This paper presents a novel approach to Bayesian nonparametric spectral analysis of stationary multivariate time series. Starting with a parametric vector-autoregressive model, the…
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…
Data Segmentation for Time Series Based on a General Moving Sum Approach
Claudia Kirch, Kerstin Reckruehm
In this paper we propose new methodology for the data segmentation, also known as multiple change point problem, in a general framework including classic mean change scenarios, cha…
Bootstrap confidence intervals for multiple change points based on moving sum procedures
Haeran Cho, Claudia Kirch
The problem of quantifying uncertainty about the locations of multiple change points by means of confidence intervals is addressed. The asymptotic distribution of the change point…
Moving sum data segmentation for stochastics processes based on invariance
Claudia Kirch, Philipp Klein
The segmentation of data into stationary stretches also known as multiple change point problem is important for many applications in time series analysis as well as signal processi…
Discussion of 'Detecting possibly frequent change-points: Wild Binary Segmentation 2 and steepest-drop model selection'
Haeran Cho, Claudia Kirch
We discuss the theoretical guarantee provided by the WBS2.SDLL proposed in Fryzlewicz (2020) and explore an alternative, MOSUM-based candidate generation method for the SDLL.
A novel change point approach for the detection of gas emission sources using remotely contained concentration data
Idris Eckley, Claudia Kirch, Silke Weber
Motivated by an example from remote sensing of gas emission sources, we derive two novel change point procedures for multivariate time series where, in contrast to classical change…
Two-stage data segmentation permitting multiscale change points, heavy tails and dependence
Haeran Cho, Claudia Kirch
The segmentation of a time series into piecewise stationary segments, a.k.a. multiple change point analysis, is an important problem both in time series analysis and signal process…
Bayesian Nonparametric Analysis of Multivariate Time Series: A Matrix Gamma Process Approach
Alexander Meier, Claudia Kirch, Renate Meyer
While there is an increasing amount of literature about Bayesian time series analysis, only a few Bayesian nonparametric approaches to multivariate time series exist. Most methods…
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…