Nested $\hat R$: Assessing Convergence for Markov chain Monte Carlo when using many short chains

google-research/google-research 25 Oct 2021

Furthermore we use $\mathfrak n \hat R$ to construct a warmup scheme with an adaptive length, allowing users to avoid running their MCMC algorithms longer than necessary.


Probabilistic Programming in Python using PyMC

pymc-devs/pymc3 29 Jul 2015

Probabilistic programming (PP) allows flexible specification of Bayesian statistical models in code.


A large-scale analysis of racial disparities in police stops across the United States

rfordatascience/tidytuesday 18 Jun 2017

We find that black drivers are stopped more often than white drivers relative to their share of the driving-age population, but that Hispanic drivers are stopped less often than whites.


HyperTools: A Python toolbox for visualizing and manipulating high-dimensional data

ContextLab/hypertools 28 Jan 2017

Just as the position of an object moving through space can be visualized as a 3D trajectory, HyperTools uses dimensionality reduction algorithms to create similar 2D and 3D trajectories for time series of high-dimensional observations.

Other Statistics

Computing Extremely Accurate Quantiles Using t-Digests

tdunning/t-digest 11 Feb 2019

We present on-line algorithms for computing approximations of rank-based statistics that give high accuracy, particularly near the tails of a distribution, with very small sketches.

Sequential Quantile Estimation Computation Data Structures and Algorithms

A flexible forecasting model for production systems

linkedin/greykite 3 May 2021

This paper discusses desirable properties of forecasting models in production systems.


Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in European countries: technical description update

ImperialCollegeLondon/covid19model 23 Apr 2020

Our model estimates these changes by calculating backwards from temporal data on observed to estimate the number of infections and rate of transmission that occurred several weeks prior, allowing for a probabilistic time lag between infection and death.

Applications Methodology

ruptures: change point detection in Python

deepcharles/ruptures 2 Jan 2018

ruptures is a Python library for offline change point detection.

Computation Mathematical Software

Orbit: Probabilistic Forecast with Exponential Smoothing

uber/orbit 18 Apr 2020

Time series forecasting is an active research topic in academia as well as industry.

Computation Methodology

Bambi: A simple interface for fitting Bayesian linear models in Python

bambinos/bambi 19 Dec 2020

The popularity of Bayesian statistical methods has increased dramatically in recent years across many research areas and industrial applications.