IBM SPSS Statistics From $79/mo 9.3 Visit ExpFamilyPCA.jl
sisl.github.io
Spec sheet
- Purpose
- ExpFamilyPCA.jl is a Julia package for exponential family principal component analysis, a generalization of PCA for non-Gaussian data.Read 12 Oct 2026 · github.com
- Free plan
- YesRead 23 Sep 2026 · sisl.github.io
- Integrations
- The documentation describes using Symbolics.jl for symbolic differentiation and Optim.jl for optimization in custom EPCA specifications.Read 12 Oct 2026 · sisl.github.io
- License
- The GitHub repository identifies the project as MIT licensed.Read 12 Oct 2026 · github.com
- Custom models
- Users can define EPCA models for custom distributions by specifying mathematical components such as an objective and link function.Read 12 Oct 2026 · sisl.github.io
- Data import formats
- Julia AbstractMatrix dataRead 23 Sep 2026 · sisl.github.io
- Input format
- The fitting and compression methods accept real-valued abstract matrices, with rows representing observations and columns representing features.Read 12 Oct 2026 · sisl.github.io
- Installation
- The project instructs users to install it through Julia's package manager with Pkg.add("ExpFamilyPCA").Read 12 Oct 2026 · sisl.github.io
- Model workflow
- EPCA objects provide fit!, compress, and decompress methods for fitting data, compressing new data, and reconstructing data.Read 12 Oct 2026 · github.com
- Optimization
- The package documents configurable optimization options, including regularization, initialization values, parameter bounds, and iteration controls.Read 12 Oct 2026 · sisl.github.io
- Performance limit
- The documentation warns that fitting may take a long time depending on dataset size and model complexity.Read 12 Oct 2026 · sisl.github.io
- Scripting support
- YesRead 23 Sep 2026 · sisl.github.io
- Support and contributions
- The project invites users to ask questions and contribute, and directs requests for new compressors or model improvements to GitHub issues.Read 12 Oct 2026 · sisl.github.io
- Supported distributions
- Built-in models cover Bernoulli, Binomial, Continuous Bernoulli, Gamma, Gaussian, Negative Binomial, Pareto, Poisson, and Weibull distributions.Read 12 Oct 2026 · sisl.github.io
- Use cases
- The project describes applications including belief compression, text analysis, denoising, sample debiasing, clustering, and dimensionality reduction.Read 12 Oct 2026 · github.com
Plans and prices
Open-source package Free Julia package · MIT license Read 12 Oct 2026 · github.com
Where Specifiction places it
- Statistical Analysis Software#75 of 1067.4
