note

Copying "Introduction to Data Analysis with Bayesian Statistical Modeling" in Python and PyMC - Vol. 14 Poisson Regression Model

Author of the book: Dr. Shinya BabaThis article is a Python transcription record of Chapter 8, Part 3, "Poisson Regression Model" from the book "Introduction to Data Analysis with Bayesian Statistical ...
GitHub

Markov Affinity-based Graph Imputation of Cells (MAGIC)

Markov Affinity-based Graph Imputation of Cells (MAGIC) is an algorithm for denoising high-dimensional data most commonly applied to single-cell RNA sequencing data. MAGIC learns the manifold data, ...
Nature

Comprehensive study on the Python-based regression machine learning models for prediction of uniaxial compressive strength using multiple parameters in Charnockite rocks

Rocks and their structures require careful planning to prevent loss of life and economic damage from human error. In civil engineering, mining, cave mining, tunneling ...
GitHub

We are hard pressed to find a concrete implementation of both Benoit Mandelbrot's "A Multifractal Model of Asset Returns" and Edgar E. Peters' "Fractal Market Analysis" so ...

This package offers time series simulation processes as well as rescaled range analysis. The time series simulations are implemented as per Benoit Mandelbrot's description in "A Multifractal Model of ...
LinkedIn

Modeling Well Transient Flow with Python

Reservoir engineers can draw some information from their reservoir by analyzing a well-test result. Well-test is an activity of opening a well to flow fluids from and into the reservoir (or production ...
LinkedIn

Simple Epidemiological Modeling in SAS, R, and Python

First off, this article is not going to show you the trajectory of the current coronavirus pandemic. I think we have enough people doing this with results all over the place. I became interested in ...