Renate Meyer

Renate Meyer

University of Auckland

H-index: 36

Oceania-New Zealand

About Renate Meyer

Renate Meyer, With an exceptional h-index of 36 and a recent h-index of 24 (since 2020), a distinguished researcher at University of Auckland, specializes in the field of Bayesian inference, state-space models, MCMC, mixture models, copula.

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

Calibrating approximate Bayesian credible intervals of gravitational-wave parameters

The use of calibration techniques in gravitational wave astronomy

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

Cosmology with the laser interferometer space antenna

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

Inference of protoneutron star properties in core-collapse supernovae from a gravitational-wave detector network

Bayesian nonparametric spectral analysis of locally stationary processes

Prospects for LISA to detect a gravitational-wave background from first order phase transitions

Renate Meyer Information

University

Position

Professor of Statistics

Citations(all)

4801

Citations(since 2020)

1580

Cited By

3747

hIndex(all)

36

hIndex(since 2020)

24

i10Index(all)

61

i10Index(since 2020)

43

Email

University Profile Page

Google Scholar

Renate Meyer Skills & Research Interests

Bayesian inference

state-space models

MCMC

mixture models

copula

Top articles of Renate Meyer

Calibrating approximate Bayesian credible intervals of gravitational-wave parameters

Physical Review D

2024/4/1

Renate Meyer
Renate Meyer

H-Index: 21

The use of calibration techniques in gravitational wave astronomy

arXiv preprint arXiv:2310.06321

2023/10/10

Renate Meyer
Renate Meyer

H-Index: 21

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

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

arXiv preprint arXiv:2306.04966

2023/6/8

Inference of protoneutron star properties in core-collapse supernovae from a gravitational-wave detector network

Physical Review D

2023/4/21

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

Prospects for LISA to detect a gravitational-wave background from first order phase transitions

Journal of Cosmology and Astroparticle Physics

2023/2/27

Renate Meyer
Renate Meyer

H-Index: 21

Figures of merit for a stochastic gravitational-wave background measurement by LISA: Implications of LISA Pathfinder noise correlations

Physical Review D

2022/9/29

Renate Meyer
Renate Meyer

H-Index: 21

Parameter estimation with gravitational waves

2022/4/8

Renate Meyer
Renate Meyer

H-Index: 21

Inference of intensity-based models for load-sharing systems with damage accumulation

IEEE Transactions on Reliability

2022/1/31

Renate Meyer
Renate Meyer

H-Index: 21

Ability of LISA to detect a gravitational-wave background of cosmological origin: The cosmic string case

Physical Review D

2022/1/10

Renate Meyer
Renate Meyer

H-Index: 21

Computational techniques for parameter estimation of gravitational wave signals

2022/1

Renate Meyer
Renate Meyer

H-Index: 21

Spectral separation of the stochastic gravitational-wave background for LISA in the context of a modulated Galactic foreground

Monthly Notices of the Royal Astronomical Society

2021/11

Astrid Lamberts
Astrid Lamberts

H-Index: 18

Renate Meyer
Renate Meyer

H-Index: 21

Bayesian spectral density estimation using P-splines with quantile-based knot placement

Computational statistics

2021/9

Renate Meyer
Renate Meyer

H-Index: 21

Inference of protoneutron star properties from gravitational-wave data in core-collapse supernovae

Physical Review D

2021/3/5

Identifying and Addressing Nonstationary LISA Noise

43rd COSPAR Scientific Assembly. Held 28 January-4 February

2021/1

Renate Meyer
Renate Meyer

H-Index: 21

Matthew Edwards
Matthew Edwards

H-Index: 2

Determining individual trajectories of joint space loss: improved statistical methods for monitoring knee osteoarthritis disease progression

Osteoarthritis and Cartilage

2021/1/1

Improved statistical methods for monitoring knee osteoarthritis disease progression.

Osteoporosis International

2020

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 Renate Meyer University(University of Auckland)

Co-Authors

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