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@dawg-at-irya Data Analysis Working Group @ IRyA/UNAM

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    18 repositories

    • Ricardo_MCMC

      Public
      Jupyter Notebook
      •
      GNU General Public License v3.0
      •0•0•0•0•Updated May 29, 2024May 29, 2024

    • hypothesis-testing

      Public
      A brief glance at hypothesis testing
      Python
      •
      GNU General Public License v3.0
      •0•0•0•0•Updated May 28, 2024May 28, 2024

    • outlier-pruning

      Public
      Gaussian Mixture Model + MCMC for fitting data with outliers
      Jupyter Notebook
      •
      GNU General Public License v3.0
      •0•0•0•0•Updated Apr 23, 2024Apr 23, 2024

    • conics-talk

      Public
      Fitting conic sections to data: Parabolae, ellipses, and hyperbolae
      Creative Commons Zero v1.0 Universal
      •0•0•0•0•Updated Mar 1, 2024Mar 1, 2024

    • error-propagation

      Public
      Error propagation: the right and the wrong
      Jupyter Notebook
      •0•0•0•0•Updated Feb 29, 2024Feb 29, 2024

    • fit-line-MCMC

      Public
      Fit a line to data using MCMC (specifically, the emcee package)
      Jupyter Notebook
      •
      GNU General Public License v3.0
      •0•0•0•0•Updated Nov 15, 2023Nov 15, 2023

    • bootstrap

      Public
      A brief presentation on bootstrap resampling
      Jupyter Notebook
      •
      GNU General Public License v3.0
      •0•0•0•0•Updated Oct 20, 2023Oct 20, 2023

    • chisq-line-fit

      Public
      Fitting a line to data: when and how to use the chi-squared
      Jupyter Notebook
      •
      GNU General Public License v3.0
      •0•0•0•0•Updated Sep 19, 2023Sep 19, 2023

    • Analysis_of_a_light_curve

      Public
      This notebook presents code for smoothing and analyzing periodic light curves, improving signal quality and eliminating noise peaks.
      Jupyter Notebook
      •0•0•0•0•Updated May 24, 2023May 24, 2023

    • data_fitting_talk

      Public
      In this talk we explain the differences between linear and non-linear models as well as ordinary least squares and non-linear least squares. Also we introduce some Python tools that can be used for fitting models to data.
      0•0•0•0•Updated May 22, 2023May 22, 2023

    • histograms-and-KDEs

      Public
      Estimating the density distributions of data using histograms and KDEs: some caveats and tips
      Jupyter Notebook
      •0•0•0•0•Updated Apr 26, 2023Apr 26, 2023

    • fits-image-axes-talk

      Public
      Presentation about how to display a FITS image with scientifically meaningful axes
      Jupyter Notebook
      •
      MIT License
      •0•0•0•0•Updated Mar 28, 2023Mar 28, 2023

    • github-copilot-talk

      Public
      A brief introduction to Github Copilot
      GNU General Public License v3.0
      •0•1•0•0•Updated Mar 23, 2023Mar 23, 2023

    • fit-line-intrinsic-spread

      Public
      Fitting a line to data with large intrinsic spread
      Python
      •
      GNU General Public License v3.0
      •0•0•0•0•Updated Mar 23, 2023Mar 23, 2023

    • chi-squared-talk

      Public
      A brief introduction to the concept of likelihood and the related chi-squared statistic
      GNU General Public License v3.0
      •0•0•0•0•Updated Mar 23, 2023Mar 23, 2023

    • color-maps-talk

      Public
      How to choose color maps for figures
      Jupyter Notebook
      •0•0•0•0•Updated Sep 17, 2019Sep 17, 2019

    • dawgi-graph-slopes

      Public
      Short presentation: "On the optimal slope of graphs (and why you should compensate your power spectra)"
      0•0•0•0•Updated Aug 20, 2019Aug 20, 2019

    • tetrabloks-talk

      Public
      Will's 10 minute presentation on "Tetrabloks – an algorithm for multi-resolution mapping of inhomogeneous data"
      0•1•0•0•Updated Jun 25, 2019Jun 25, 2019