Claudia Kirch

About Claudia Kirch

Claudia Kirch, With an exceptional h-index of 25 and a recent h-index of 19 (since 2020), a distinguished researcher at Otto-von-Guericke-Universität Magdeburg, specializes in the field of Time Series Analysis, Change Point Analysis, Data Segmentation, Computational Statistics, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Data segmentation for time series based on a general moving sum approach

Ein Praxisbericht zur Kombination digitaler Elemente mit interaktiven Präsenzzeiten in der Mathematik-Lehre

The state of cumulative sum sequential change point testing seventy years after Page

Scan statistics for the detection of anomalies in M-dependent random fields with applications to image data

Posterior consistency for the spectral density of non‐Gaussian stationary time series

Variations of the depth based Liu-Singh two-sample test including functional spaces

A nonparametrically corrected likelihood for Bayesian spectral analysis of multivariate time series

Editorial for the special issue on Time Series Analysis

Claudia Kirch Information

University

Position

Institute for Mathematical Stochastics

Citations(all)

1628

Citations(since 2020)

926

Cited By

1120

hIndex(all)

25

hIndex(since 2020)

19

i10Index(all)

31

i10Index(since 2020)

27

Email

University Profile Page

Google Scholar

Claudia Kirch Skills & Research Interests

Time Series Analysis

Change Point Analysis

Data Segmentation

Computational Statistics

Machine Learning

Top articles of Claudia Kirch

Data segmentation for time series based on a general moving sum approach

Annals of the Institute of Statistical Mathematics

2024/3/14

Claudia Kirch
Claudia Kirch

H-Index: 16

Ein Praxisbericht zur Kombination digitaler Elemente mit interaktiven Präsenzzeiten in der Mathematik-Lehre

Mitteilungen der Deutschen Mathematiker-Vereinigung

2023/12/30

Frank Aurzada
Frank Aurzada

H-Index: 14

Claudia Kirch
Claudia Kirch

H-Index: 16

The state of cumulative sum sequential change point testing seventy years after Page

Biometrika

2023/12/21

Claudia Kirch
Claudia Kirch

H-Index: 16

Scan statistics for the detection of anomalies in M-dependent random fields with applications to image data

arXiv preprint arXiv:2311.09961

2023/11/16

Claudia Kirch
Claudia Kirch

H-Index: 16

Philipp Klein
Philipp Klein

H-Index: 2

Posterior consistency for the spectral density of non‐Gaussian stationary time series

Scandinavian Journal of Statistics

2023/9

Claudia Kirch
Claudia Kirch

H-Index: 16

Renate Meyer
Renate Meyer

H-Index: 21

Variations of the depth based Liu-Singh two-sample test including functional spaces

arXiv preprint arXiv:2308.09869

2023/8/19

Claudia Kirch
Claudia Kirch

H-Index: 16

A nonparametrically corrected likelihood for Bayesian spectral analysis of multivariate time series

arXiv preprint arXiv:2306.04966

2023/6/8

Editorial for the special issue on Time Series Analysis

2023/5

Bayesian nonparametric spectral analysis of locally stationary processes

arXiv preprint arXiv:2303.11561

2023/3/21

Claudia Kirch
Claudia Kirch

H-Index: 16

Renate Meyer
Renate Meyer

H-Index: 21

Sequential change point tests based on U‐statistics

Scandinavian Journal of Statistics

2022/9

Claudia Kirch
Claudia Kirch

H-Index: 16

Two-stage data segmentation permitting multiscale change points, heavy tails and dependence

Annals of the Institute of Statistical Mathematics

2022/8/1

Haeran Cho
Haeran Cho

H-Index: 10

Claudia Kirch
Claudia Kirch

H-Index: 16

Asymptotic delay times of sequential tests based on U-statistics for early and late change points

Journal of Statistical Planning and Inference

2022/12/1

Claudia Kirch
Claudia Kirch

H-Index: 16

Bootstrap confidence intervals for multiple change points based on moving sum procedures

Computational Statistics & Data Analysis

2022/11/1

Haeran Cho
Haeran Cho

H-Index: 10

Claudia Kirch
Claudia Kirch

H-Index: 16

Data segmentation algorithms: Univariate mean change and beyond

Econometrics and Statistics

2021/11/2

Haeran Cho
Haeran Cho

H-Index: 10

Claudia Kirch
Claudia Kirch

H-Index: 16

Alexander G. Tartakovsky (2020): Sequential change detection and hypothesis—general non-iid stochastic models and asymptotically optimal rules: CRC Press, 2019, 320 pp. $140 …

2021/6

Claudia Kirch
Claudia Kirch

H-Index: 16

Detecting changes in the covariance structure of functional time series with application to fMRI data

Econometrics and Statistics

2021/4/1

Claudia Kirch
Claudia Kirch

H-Index: 16

Moving sum data segmentation for stochastics processes based on invariance

arXiv preprint arXiv:2101.04651

2021/1/12

Claudia Kirch
Claudia Kirch

H-Index: 16

Philipp Klein
Philipp Klein

H-Index: 2

Discussion of ‘Detecting possibly frequent change-points: Wild Binary Segmentation 2 and steepest-drop model selection’

Journal of the Korean Statistical Society

2020/12

Haeran Cho
Haeran Cho

H-Index: 10

Claudia Kirch
Claudia Kirch

H-Index: 16

A novel change-point approach for the detection of gas emission sources using remotely contained concentration data

2020/9/1

Claudia Kirch
Claudia Kirch

H-Index: 16

Bayesian nonparametric analysis of multivariate time series: a matrix gamma process approach

Journal of Multivariate Analysis

2020/1/1

Claudia Kirch
Claudia Kirch

H-Index: 16

Renate Meyer
Renate Meyer

H-Index: 21

See List of Professors in Claudia Kirch University(Otto-von-Guericke-Universität Magdeburg)

Co-Authors

academic-engine