Bayesian reasoning is applied to the data by the ROG Collaboration, in which grav-itational wave (g.w.) signals are searched for in a coincidence experiment between Explorer and Nautilus. The use of Bayesian reasoning allows, under well defined hy-potheses, even tiny pieces of evidence in favor of each model to be extracted from the data. The combination of the data of several experiments can therefore be performed in an optimal and efficient way. Some models for Galactic sources are considered and, within each model, the experimental result is summarized with the likelihood rescaled to the insensitivity limit value ( “ function”). The model comparison result is given in in terms of Bayes factors, which quantify how the ratio of beliefs a...
Hypothesis testing is a special form of model selection. Once a pair of competing models is fully de...
We illustrate some statistical challenges in Astrophysics and Cosmology, inparticular noting the app...
We present a general framework for incorporating astrophysical information into Bayesian parameter e...
Bayesian reasoning is applied to the data by the ROG Collaboration, in which gravitational wave (gw)...
Second-generation interferometric gravitational-wave detectors, such as Advanced LIGO and Advanced V...
Second-generation interferometric gravitational-wave detectors, such as Advanced LIGO and Advanced V...
Bayesian methods are being increasingly employed in many different areas of research in the physical...
The Bayesian approach to probability theory is presented as an alternative to the currently used lon...
Model comparison in the modern era allows us to use statistical methods that were previously difficu...
This thesis consists of two main parts, both of which focus on Bayesian methods and the problem of m...
Gravitational-wave data analysis demands sophisticated statistical noise models in a bid to extract ...
. The Bayesian approach to probability theory is presented as an alternative to the currently used l...
Rigorously quantifying the information in high-contrast imaging data is important for informing foll...
In the context of data modeling and comparisons between different fit models, Bayesian analysis call...
The timing of radio pulsars in binary systems provides a superb testing ground of general relativity...
Hypothesis testing is a special form of model selection. Once a pair of competing models is fully de...
We illustrate some statistical challenges in Astrophysics and Cosmology, inparticular noting the app...
We present a general framework for incorporating astrophysical information into Bayesian parameter e...
Bayesian reasoning is applied to the data by the ROG Collaboration, in which gravitational wave (gw)...
Second-generation interferometric gravitational-wave detectors, such as Advanced LIGO and Advanced V...
Second-generation interferometric gravitational-wave detectors, such as Advanced LIGO and Advanced V...
Bayesian methods are being increasingly employed in many different areas of research in the physical...
The Bayesian approach to probability theory is presented as an alternative to the currently used lon...
Model comparison in the modern era allows us to use statistical methods that were previously difficu...
This thesis consists of two main parts, both of which focus on Bayesian methods and the problem of m...
Gravitational-wave data analysis demands sophisticated statistical noise models in a bid to extract ...
. The Bayesian approach to probability theory is presented as an alternative to the currently used l...
Rigorously quantifying the information in high-contrast imaging data is important for informing foll...
In the context of data modeling and comparisons between different fit models, Bayesian analysis call...
The timing of radio pulsars in binary systems provides a superb testing ground of general relativity...
Hypothesis testing is a special form of model selection. Once a pair of competing models is fully de...
We illustrate some statistical challenges in Astrophysics and Cosmology, inparticular noting the app...
We present a general framework for incorporating astrophysical information into Bayesian parameter e...