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

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

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 coefficient 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 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

Compute a sample Pearson product-moment correlation distance.

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.

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

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.

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.

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.