Entries by Orbifold

Stochastic integrals via R

The rules for random things are somewhat different than the ones you know for ‘smooth’ things. In a university course you get proofs based on Martingales, Wiener measures and whatnot but it all can feel very abstract. Even the basic examples can be confusing. So, here I want to show you that without knowing any high-tech maths you can see from basic examples in R how and that it works.

Reproducible research

Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. In the more narrow context of data science consultancy it means you package things in such a way that the customer can re-run […]

Pearson p-value

Numerical algorithms and statistical theory is quite robust and universal, but once you look into the various software implementations you discover that presumed standards are not so universal.

Graph databases

The shortlist of graph databases I keep an eye on. Many other NoSQL engines can store graph-like data, of course. Neo4j Neo4j is a graph database boasting massive performance improvements versus relational databases. It is very agile and fast. At the moment it is used by many startups in applications such as  social platforms, fraud […]