statistical-inference

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

Code for modelling estimated deaths and cases for COVID19.

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

pure-Python HistFactory implementation with tensors and autodiff

My Solutions to 120 commonly asked data science interview questions.

Estimagic is a Python package for nonlinear optimization with or without constraints. It is particularly suited to solve difficult nonlinear estimation problems. On top, it provides functionality to perform statistical inference on estimated parameters.

Ambrosia is a Python library for A/B tests design, split and result measurement

A resource list for causality in statistics, data science and physics

MCMC sample analysis, kernel densities, plotting, and GUI

R package for statistical inference using partially observed Markov processes

Hypothesis and statistical testing in Python

Statistics tools and utilities.

Basic statistical modelling examples.

Statistical inference on machine learning or general non-parametric models

Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. Learn statistical concepts that are very important to Data science domain and its application using Python. Learn about Numpy, Pandas Data Frame.

Probabilistic Threshold-Free Cluster Enhancement of Neuroimages

Pure julia implementation of Multiple Affine Invariant Sampling for efficient Approximate Bayesian Computation

Code and data for the KDD2020 paper "Learning Opinion Dynamics From Social Traces"

Texomer: Integrating Analysis of Cancer Genome and Transcriptome Sequencing Data