Programming & Scientific Computing · Statistical & Parallel Computing

Advanced statistical computing — Reproducibility, development, and version control

Public introduction · full guide in Eikos

Introduction

What this guide covers

An expert-level theoretical and methodological reference on the integration of advanced software engineering into analytical and scientific processes.

Overview

Topics covered

  • Introduction
  • Statistical Computing: Reproducibility, Development and Version Control
  • Philosophy of Reproducibility and the Analytical Crisis
  • Management of Computational Environments and Dependencies
  • The Hierarchy of Abstraction in the Analytical Infrastructure
  • Control of Interpreter Dependencies: Lockfiles and Manifests

Related concepts

Main connections

  • Linear algebra & matrices
  • Bootstrap resampling
  • Computational reproducibility & provenance
  • Survival analysis & Kaplan-Meier
  • Maximum likelihood estimation
  • Variance & standard deviation

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

ℱ(𝒟;Θ,ℰ)⟶ℛ
View LaTeX source\mathcal{F}(\mathcal{D}; \Theta, \mathcal{E}) \longrightarrow \mathcal{R}