Beast code in Giters

Brian's repositories

all-of-statistics

Solutions to Wasserman's 'All of Statistics'.

Language:Jupyter Notebook100 90

bayesian-data-analysis

Berlin Bayesians' solutions to Bayesian Data Analysis, 3rd edition.

Language:HTML18 50

I often post solutions to textbook exercises, including: Bayesian Data Analysis (BDA) by Gelman et al; Causal Inference in Statistics Primer (CISP) by Pearl et al; Purely Functional Data Structures (PFDS) by Okasaki.

Language:HTML6 10

okasaki-pfds

Solutions to Okasaki's "Purely Functional Data Structures":

Language:HaskellGPL-3.06 10

berlin-marathon

Some scripts to scrape and clean berlin marathon data.

Language:Jupyter Notebook4 2 1

berlin_bayesians_workshop_map_rect

Presentation for the Berlin Bayesians introduction to map_rect

Language:CSS3 10

semipyrametric-statistics

Python implementations of semiparametric statistical techniques.

Language:Python3 30

fit-parser

A parser for Garmin's FIT format.

Language:HaskellGPL-3.01 10

BDA_course_Aalto

Bayesian Data Analysis course at Aalto

Language:TeX010

cmdstanpy

CmdStanPy is a lightweight interface to Stan for Python users which provides the necessary objects and functions to compile a Stan program and fit the model to data using CmdStan.

Language:PythonBSD-3-Clause000

prob-stats

Probability and Statistics: a simulation-based introduction. An open-access book.

Language:TeXBSD-3-Clause010

prophet

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

Language:PythonMIT000

stappit.github.io

My blog is not longer hosted on gitpages. See:

Language:HTML010

statrethinking_reading_group

Material for the Berlin Bayesian reading group covering Statistical Rethinking by Richard McElreath

MIT000

statrethinking_winter2019

Statistical Rethinking course at MPI-EVA from Dec 2018 through Feb 2019

000

wood_gam

Some solutions to Wood's Generalised Additive Models book.

010