Code for SIGGRAPH 2024 (ToG) paper "Specular Polynomials"

A Stata package for bi-variate maps

Bivariate histogram plot from polar coordinates / position vectors in MATLAB.

metaanalysis projects

Fast streaming univariate and bivariate moments and t-statistics

Complex / 2d multivariate bivariate colormap / Domain coloring for Matplotlib, Plotly etc. (pure-numpy)

Demonstration of the Gaussian Mixture Model (GMM) for the bivariate normal distribution along with a derivation of the E and M steps.

Compute a moving sample Pearson product-moment correlation distance incrementally.

I Learnt how to make regression for bivariate data in my Statistics class today, So I made a small program to do the same, it takes x and y arrays and outputs a linear equation with slope and constant.

Compute a moving sample Pearson product-moment correlation coefficient incrementally.

This software package creates subdivision matrices for generalized quadratic and cubic B-spline subdivision for subdivision surfaces as well as subdivision volumes. The subdivision matrices define refinement rules for arbitrary combinatorial structures. The matrices have a valid eigenstructure and a subdominant eigenvalue of 1/2.

Compute a sample Pearson product-moment correlation distance.

Compute a sample Pearson product-moment correlation coefficient.

Strip Plot, Grouping with Strip Plot, Swarm Plot, Box and Violin Plot, placing plots together, Combining the plots, Joint Plot, Density Plot, Pair Plot

PISA 2012 data visualisation. Univariate, bivariate and multivariate exploration.

Animate Bivariate Normal Distribution using JAX and Matplotlib and making it interactive using ipywidgets.

Enhance XYZ shop's delivery efficiency by evaluating five delivery services using a comprehensive dashboard to gain insights to improve the selection of delivery service companies.

Polynomials are mathematical objects which are expressions of variables and coefficients added to-gether. These polynomials can use operator overloading in a very intuitive manner since most of the operators that we can overload are mathematical operators, which can also be applied to polynomials.

Used libraries and functions as follows:

Segmentación de usuarios de una app bancaria en Colombia. Incluye EDA univariado y bivariado, y clustering con K-Means. Permite identificar perfiles de clientes y proponer estrategias de marketing, retención y cross-selling.

Map showing where Trump voters would be most impacted by medicaid cuts

The analysis focused on segmenting a specific group of mall customers using the KMeans unsupervised machine learning algorithm. Univariate, bivariate, and multivariate clusters were identified and analyzed using summary statistics to gain insights into customer behavior and determine the most valuable segment for targeted marketing strategies.