There are 3 repositories under astrostatistics topic.
Astrostatistics and Machine Learning class for the MSc degree in Astrophysics at the University of Milan-Bicocca (Italy)
Astrostatistics class for the MSc degree in Astrophysics at the University of Milan-Bicocca (Italy)
Functional Posterior Plotter
Astrostatistics and Machine Learning class for the MSc degree in Astrophysics at the University of Milan-Bicocca (Italy)
Better Radial velocities from Stellar Spectroscopy via Machine Learning
python package to measure power spectrum and bispectrum
An efficient Python implementation for Bayesian inference in binary stars based on Stan.
Scalpels algorithm
Computes Cross Correlation Functions (CCFs) with RvSpectML
Programs and files written for Astrostatistics for IB Physics IA. Topic: Visualizing and analyzing the habitable zones for 150,000 stars from the hipparcos catalogue.
Research presentations on Astronomy and Astrostatistics
Base package to be imported by other members of RvSpectML ecosystem
Variable Star Signature Classification using Slotted Symbolic Markov Modeling
This repository contains all the code (in the form of Jupyter Notebooks) to reproduce the results in our paper, "Light Curve Classification with DistClassiPy: a new distance-based classifier"
ASG Chicago website
Lightcurve Classification for Periodically Varying Stars (SAMSI Undergraduate Workshop Project)
This repository contains the documentation and archived code to create TolTEC simulated maps using the SIDES catalog (Bethermin et al. 2017) and the source extraction algorithm used for analyzing these maps.
Personal homepage
Project aims at modeling the size distribution of sunspots greater than 60 millionths of a solar hemisphere (MSH) using a truncated log-normal distribution.
Instrument-speciifc code for RvSpectML
Repo for RvSpectML code still in the experimental stage
Scripts for analyzing NEID Sun-as-a-star observations using RVSpectML
README for RvSpectML project
Plotting functions/scripts for use with RvSpectML
The initial analysis of LINEAR data using supervised classification methods.
O'Connell Effect Detector using Push-Pull Learning
Project Repository for IB physics extended essay
Statistically Quantifying Difference in the Observable Universe under Warm and Cold Dark Matter Assumptions
Project aims to determine the binary star fraction in the Globular Cluster NGC 5053 using data from 66 stars observed over three years using bayesian statistical inference.
Project aims to estimate Hubble's constant by performing a linear regression analysis of redshifts and distances of Type Ia supernovae within a redshift of 0.1