X-PSI: X-ray Pulse Simulation and Inference
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Updated
May 28, 2024 - Python
X-PSI: X-ray Pulse Simulation and Inference
Toolbox for non-linear calibration modeling.
Matrix Determinant Toolkit
Provides likelihood functions for Gaussian Processes.
Modelling extreme values
This aim of this project is to analyze globular star clusters in the Milky Way, in order to understand their dynamics. The conducted study examined the properties that affect the central velocity dispersion, their impact and the correlations between them.
A repository for the 'concurve' R package which generates confidence distributions and likelihood functions. Includes documentation on how to do produce similar graphs for Stata.
Dynamic failure rate distributions (DFR)
Likelihood to account for Monte Carlo statistical uncertainties
Eindhoven University of Technology (TU/e) course "Improving your statistical inferences" by Daniel Lakens on Coursera (completed Dec 2022).
Here for a small dataset we have used OLS(Ordiniary Least Square) and MLE(Maximum likelihood Estimation ) to calculate the regression parameters slope(b1),intercept(b0) and standard deviation of reisduals.At the end we can conclude that both the methods of estimation produces the same result.
The maximum likelihoood estimator approach is used here for calculating the Regression parameter that is slope(b1),intercept(b0) and standard deviation of error/residuals. Then Result or the output for the regression parameters using the OLS(ordiniary Least Sqaure) estimation method versus the MLE(MAximum Likelihood Estimation) method is compare…
Formulate likelihood problems and solve them with maximum likelihood estimation (MLE)
Parallel Metropolis-Hastings Markov chain Monte Carlo toolkit
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