philentropy review
A focused open-source R package for comparing probability functions and calculating information measures.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
For analysts working in R, philentropy is an open-source package for comparing univariate or multivariate probability functions. Its focus is specific: it calculates distances and similarities between probability distributions, plus information-theory measures. The package suits solo users and small teams whose statistical, clustering, classification or machine-learning work involves probability vectors. It is not a general-purpose statistical analysis application.
Its breadth within that focus is the main draw. The package supplies 46 probability-distance and similarity measures, including Euclidean, cosine, Jaccard, Hellinger, Kullback–Leibler and Jensen–Shannon measures. It can create pairwise distance matrices, estimate probability vectors from counts, and calculate Shannon, joint and conditional entropy, mutual information and generalized Jensen–Shannon divergence. Distance-diversity calculations across probability density functions extend the analysis beyond a single comparison. Inputs are R matrices or data frames, and functions can be used in scripts for statistical inference and goodness-of-fit work as well as clustering and classification.
The open-source package has no cost, and its published offering is not organized into paid tiers. Its fit depends on an R-based workflow: it is a desktop and self-hosted package for Windows and macOS, not a hosted application. Documentation is the listed support channel. Choose philentropy when you need a substantial selection of probability distances or information measures inside R; choose a broader statistics platform if you need general analysis capabilities or a hosted interface.
philentropy pros and cons
- Where it wins
- Provides 46 probability-distance and similarity measures.
- Calculates entropy, mutual information and Jensen–Shannon divergence.
- Supports R matrices and data frames in scripts.
- Where it doesn't
- Focused on probability functions, not general statistical analysis.
- Requires R scripts rather than a hosted statistical application.
- Deployment is limited to desktop and self-hosted use.
philentropy fact sheet, pricing and score →
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